Cloud storage methods and systems

ABSTRACT

Programmer input in a programming language is received, the programmer input for adding data to an electronic storage object that is accessible via a network. The programmer input includes i) a built-in function corresponding to adding data to electronic storage objects, ii) a first parameter specifying the electronic object to which data is to be stored, and iii) one or more second parameters indicating the data that is to be stored. The programmer input is evaluated with a computational application to generate one or more messages to a server for the server to add the data to the electronic object, and the one or more messages are sent to cause the data indicated by the second parameter to be added to the electronic storage object.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/121,278, now U.S. Pat. No. 11,265,378, entitled “Cloud StorageMethods and Systems,” filed on Dec. 14, 2020, which is a continuation ofU.S. patent application Ser. No. 16/666,146, now U.S. Pat. No.10,868,866, entitled “Cloud Storage Methods and Systems,” filed on Oct.28, 2019, which is a continuation of U.S. patent application Ser. No.15/589,266, now U.S. Pat. No. 10,462,222, entitled “Cloud StorageMethods and Systems,” filed on May 8, 2017, which is a continuation ofU.S. patent application Ser. No. 14/872,129, now U.S. Pat. No.9,646,003, entitled “Cloud Storage Methods and Systems,” filed Sep. 30,2015, which is a continuation-in-part of U.S. patent application Ser.No. 14/549,541, entitled “Methods and Systems for Cloud Computing,”filed Nov. 20, 2014, which claims the benefit of U.S. ProvisionalApplication No. 61/906,888, entitled “Cloud Computing Platform,” filedon Nov. 20, 2013. All of the applications referenced above are herebyincorporated by reference herein in their entireties.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to cloud computing, and moreparticularly, systems that enable adding data to and retrieving datafrom objects in cloud storage, and processing the retrieved data.

BACKGROUND

The present availability of high-capacity networks, computing power, andstorage, as well as the widespread adoption of hardware virtualization,service-oriented architecture, and autonomic and utility computing haveled to a growth in cloud computing.

In cloud computing, multiple remote servers (usually a large number) arenetworked to allow centralized data storage and online access tocomputer services or resources. Cloud resources are typically shared bymultiple users and also dynamically reallocated based on demand.

Software as a service (SaaS) is a category of cloud computing servicesin which software is centrally hosted and provided as a service. SaaS istypically accessed by users using a thin client via a web browser.Typically, a single version of the application is used for allcustomers, although customization of the application may be accomplishedby selecting from a set of predefined configuration options. Thus, SaaSsystems are inflexible.

Platform as a Service (PaaS) is a category of cloud computing servicesin which a computing platform and a solution stack are provided as aservice. In PaaS, a provider provides a user with tools and/or librariesfor creating an application or service to be hosted on the provider'splatform, i.e., servers, storage, and other services that are requiredto host users' applications. Since PaaS systems typically support only alimited number of programming languages and frameworks, however,adopting a PaaS system may require utilizing an unfamiliar languageand/or programming framework.

Online file storage, or cloud storage, allows a user to store files on aremote server or servers and later access the files. For example, a usercan upload files, and the files can later be accessed over the Internetfrom the same computer or a different computer, by the same user orsometimes by other users. Many cloud storage providers utilize an objectstorage architecture that manages data as objects.

SUMMARY OF THE DISCLOSURE

In an embodiment, a method for creating a cloud storage object forstoring data, and retrieving data from the cloud storage objectincludes: receiving, at one or more processors, one or more applicationprogramming interface (API) calls requesting creation of an electronicstorage object that is accessible on a network, the one or more APIcalls including i) an indication of the request to create the electronicstorage object, and ii) one or more parameters indicating how datasubsequently received by a server for storage in the electronic storageobject is to be interpreted by a computational application; andresponsive to the one or more API calls, creating, with the one or moreprocessors, the electronic storage object in a database so that theelectronic storage object is accessible on the network. Creating theelectronic storage includes storing metadata in the electronic storageobject that indicates how the data subsequently received by the serverfor storage in the electronic storage object is to be interpreted by thecomputational application. The method also includes: receiving, at theone or more processors, one or more messages corresponding to requeststo access data in the electronic storage object; and responsive to theone or more messages: locating, at one or more processors, theelectronic storage object in the database based on the one or moremessages, retrieving, at the one or more processors, data from theelectronic storage object, and forwarding, with the one or moreprocessors and via a communication network, the retrieved data to acomputer that executes the computational application, the retrieved databeing in a format recognized by the computational application.

In another embodiment, a system comprises: a network interface deviceconfigured to support communications via a communication network; anetwork-accessible computer storage system; one or more processorscoupled to the network interface device and the network-accessiblecomputer storage system; and one or more memory devices coupled to theone more processors. The one or more memory devices storing machinereadable instructions that, when executed by the one or more processors,cause the one or more processors to: receive, via the network interfacedevice, one or more application programming interface (API) callsrequesting creation of an electronic storage object that is accessibleon the communication network, the one or more API calls including i) anindication of the request to create the electronic storage object, andii) one or more parameters indicating how data subsequently received bya server for storage in the electronic storage object is to beinterpreted by a computational application; and responsive to the one ormore API calls, create the electronic storage object in thenetwork-accessible computer storage system so that the electronicstorage object is accessible on the communication network. Creating theelectronic storage object in the network-accessible computer storagesystem includes storing metadata in the electronic storage object thatindicates how the data subsequently received by the server for storagein the electronic storage object is to be interpreted by thecomputational application. The one or more memory devices further storemachine readable instructions that, when executed by the one or moreprocessors, cause the one or more processors to: receive, via thenetwork interface device, one or more messages corresponding to requeststo access data in the electronic storage object, the one or moremessages corresponding to the electronic storage object from which datais to be accessed, and responsive to the one or more messages: locatethe electronic storage object in the network-accessible computer storagesystem based on the one or more messages, retrieve data from theelectronic storage object, and forward, via the network interface deviceand via the communication network, to a computer that executes acomputational application, the retrieved data being in a formatrecognized by the computational application.

In yet another embodiment, a method includes: receiving, at one or moreprocessors, first messages corresponding to requests to add data to aplurality of electronic storage objects that are accessible on anetwork, each first message corresponding to the electronic storageobject to which data is to be stored, and each first message includingrespective raw data corresponding to the respective data that is to bestored, wherein the first messages correspond to requests to add datafrom multiple different applications; and responsive to first messages:locating, at one or more processors, electronic storage objects in adatabase based on the first messages, identifying, at one or moreprocessors, respective data conversion metadata in the electronicstorage objects that indicate how the raw data is to be converted toformatted data in a format that is recognized by a computationalapplication, using the data conversion metadata to convert, at one ormore processors, the raw data to the formatted data in the formatrecognized by the computational application, and storing the formatteddata to the electronic storage objects in the database. The method alsoincludes: receiving, at one or more processors, second messagescorresponding to requests to access data in the electronic storageobjects, the second messages corresponding to electronic storageobjects, the second messages being received from a plurality ofinstances of the computational application executing on one or moreprocessors; and responsive to the second messages: locating, at one ormore processors, respective electronic storage objects in the databasebased on the second messages, retrieving, at the one or more processors,data from the electronic storage objects, and forwarding, with the oneor more processors, the retrieved data in the format recognized by thecomputational application to the plurality of instances of thecomputational application.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram of an example system for a cloud-based storagesystem, according to an embodiment.

FIG. 2A is an example of programmer input utilized to create a cloudstorage object, according to an embodiment.

FIG. 2B is another example of programmer input utilized to create acloud storage object, according to another embodiment.

FIG. 2C is another example of programmer input utilized to create acloud storage object, according to another embodiment.

FIG. 2D is yet another example of programmer input utilized to create acloud storage object, according to yet another embodiment.

FIG. 3 is an example of an electronic file system structure of a cloudstorage object, according to an embodiment.

FIG. 4 is a flow diagram of an example method for creating a cloudstorage object, according to an embodiment.

FIG. 5A is an example of programmer input utilized to add data to acloud storage object, according to an embodiment.

FIG. 5B is another example of programmer input utilized to add data to acloud storage object, according to another embodiment.

FIG. 6 is a flow diagram of an example method for adding data to a cloudstorage object, according to an embodiment.

FIG. 7 is a flow diagram of another example method for adding data to acloud storage object, according to another embodiment.

FIG. 8A illustrates an example web application programming interface(API) call for adding data to a cloud storage object, according to anembodiment.

FIG. 8B illustrates another example web API call for adding data to a c,according to another embodiment.

FIG. 9A illustrates an example in which data is added to a cloud storageobject using email, according to an embodiment.

FIG. 9B illustrates another example in which data is added to a cloudstorage object using email, according to another embodiment.

FIG. 9C illustrates another example in which data is added to a cloudstorage object using email, according to another embodiment.

FIG. 9D illustrates yet another example in which data is added to acloud storage object using email, according to yet another embodiment.

FIG. 10A illustrates an example in which data is added to a cloudstorage object using Twitter®, according to an embodiment.

FIG. 10B illustrates another example in which data is added to a cloudstorage object using Twitter®, according to another embodiment.

FIG. 11 is a block diagram of a sensor device that is configured to adddata to a cloud storage object, according to an embodiment.

FIG. 12 is an example of programmer input utilized to retrieve data froma cloud storage object and analyze the retrieved data, according to anembodiment.

FIG. 13 is another example of programmer input utilized to retrieve datafrom a cloud storage object and analyze the retrieved data, according toan embodiment.

FIG. 14 is a flow diagram of an example method for retrieving data froma cloud storage object, according to another embodiment.

FIGS. 15A and 15B illustrate an example web page that displays resultsof analyses and/or operations performed on data in an example cloudstorage object, according to another embodiment.

FIGS. 16A and 16B illustrate an example web page that allows a user toselect a cloud storage object, and then displays results of analysesand/or operations performed on the cloud storage object, according toanother embodiment.

FIG. 17A is an example of programmer input utilized to create and deploya web form for accepting data and then storing the data to a cloudstorage object, according to an embodiment.

FIG. 17B is an example web form created based on the programming inputof FIG. 17A, according to an embodiment.

DETAILED DESCRIPTION

FIG. 1 is a diagram of an example system 100 for creating storageobjects, modifying the objects (e.g., adding data to, changing data in,removing data from, etc., the objects), and/or retrieving data from theobjects, according to an embodiment. The system 100 may make storageobjects privately and/or publicly available via a network such as anintranet, an extranet, a wide area network (WAN), the Internet, etc. Invarious embodiments, the system 100 facilitates creation of objects thatcan be accessed via a network, modifying already created objects via thenetwork (e.g., adding data to already created objects via a network,removing data from already created objects via a network, changing datain already created objects via a network, etc.), reading data fromalready created objects via the network, etc. The storage objectsdescribed herein are termed “cloud storage objects” to emphasize thatthe storage objects are accessible via a network.

In some embodiments, the system 100 is configured to format cloudstorage objects in a unified format recognized by a computationalapplication, such that cloud storage objects can include data of avariety of types and such that the computational application can readilyprocess the data in the variety of types, which are recognized by thecomputational application. For example, in one embodiment, thecomputational application is the MATHEMATICA® computational system,which is a powerful computational tool that can evaluate generalsymbolic expressions, as well as mathematical and numeric expressions. Aunifying feature of MATHEMATICA® is that everything is internallyrepresented as a symbolic expression, with all more specific data typestreated as special cases—symbols to which additional rules apply.MATHEMATICA® utilizes the Wolfram Language™, which is an interpretedlanguage, and evaluates symbolic expressions that are expressed usingthe Wolfram Language™. In some embodiments, evaluation of a symbolicexpression involves applying to the symbolic expression alltransformation rules that fit that expression.

In an embodiment, the system 100 includes one or more computers, such asa computer 102. The computer 102 includes one or more processors 104 andone or more memory devices 108. The computer 102 also includes, or iscoupled to, one or more input devices 112. Additionally, the computer102 includes, or is coupled to, one or more display devices 116. In someembodiments, the computer 102 includes one or more network interfacedevices 120. The one or more processors 104, the one or more memorydevices 108, the one or more input devices 112 (sometime referred toherein as “the input device 112” for brevity), the one or more displaydevices 116 (sometime referred to herein as “the display device 116” forbrevity), the one or more network interface devices 120 (sometimereferred to herein as “the network interface device 120” for brevity),etc., may be communicatively coupled via one or more busses 124(sometime referred to herein as “the bus 124” for brevity). In otherembodiments, the computer 102 may have other suitable structures and/orcomponents.

The one or more processors 104 (sometime referred to herein as “theprocessor 104” for brevity) may comprise one or more general purposeprocessors (e.g., a central processing unit), one or more specialpurpose processors (e.g., a co-processor, a graphics processor, etc.).At least one of the one or more processors 104 executes machine readableinstructions stored in the memory 108. The one or more memory devices108 (sometime referred to herein as “the memory 108” for brevity)include one or more of random access memory (RAM), read only memory(ROM), a FLASH memory, a magnetic disk drive, an optical disk drive,etc.

The one more input devices 112 include one or more suitable inputdevices such as a keyboard, a key pad, a mouse, a trackball, one or morebuttons, a touch screen that overlays a display device, etc. The one ormore network interface devices 120 comprise one or more suitable networkinterface devices (NICs) such as a wired network NIC, a wireless networkNIC, etc.

In some embodiments, the memory 108 may store a computationalapplication 140 such as the MATHEMATICA® computational application fromWolfram Research, Inc., a spreadsheet application, etc., where thecomputational application 140 is configured to cause a cloud serversystem (discussed in more detail below) to create cloud storage objectsand/or to modify cloud storage objects. For example, in an embodiment,the computational application 140 may include a cloud storage front end144 that enables creation and/or modification of cloud storage objects(via interaction with the cloud server system), according to variousembodiments. In some embodiments, the computational application 140 isconfigured to provide an electronic user interface such as a workspace(e.g., a notebook, a spreadsheet, a document, etc.) in which a user canenter software code and/or functions to be evaluated, cause thefunctions to be evaluated, and/or view results of the evaluations. Insome embodiments, a user can enter software code and/or functions in theworkspace, where the software code and/or functions cause the cloudserver system to create cloud storage objects and/or to modify cloudstorage objects.

In some embodiments, however, the computational application 140 isomitted and the cloud storage front end 144 is a standalone applicationand/or module. In some embodiments, the cloud storage front end 144 isincorporated into another suitable application different than thecomputational application 140. In some embodiments, the cloud storagefront end 144 is a web browser, and a user can cause the cloud serversystem to create cloud storage objects and/or to modify cloud storageobjects via the web browser. In some embodiments, the cloud storagefront end 144 is a communication application (e.g., an emailapplication, a text messaging application, etc.), and a user can causethe cloud server system to modify cloud storage objects via thecommunication application, as will be discussed in more detail below. Ifother computers (not shown) similar to the computer 102 are included,one or more of the other computers may include respective cloud storagefront ends 144.

In various embodiments, the computer 102 comprises a desktop computer, aworkstation, a laptop computer, a tablet computer, a smart phone, apersonal digital assistant, a gaming system, a server, etc. If othercomputers (not shown) similar to the computer 102 are included, theother computers may be of various types.

In some embodiments, the computer 102 (and, optionally, one or moreother computers) is coupled to a network 150. The network 150 maycomprise one or more of a local area network (LAN), a wide area network(WAN), a metropolitan area network (MAN), a mobile communicationsnetwork, an intranet, an extranet, the Internet, etc.

In some embodiments, the system 100 may include one or more servers suchas the server 152. FIG. 1 illustrates a single server 152 for brevity,but the system 100 includes multiple other similarly configured serversin some embodiments. In some embodiments, multiple servers (includingthe server 152) are networked together to provide online access to datastorage via the network 150. One server 152 will be discussed in detailwith respect to FIG. 1, and other servers (if included) have the same ora similar suitable structure, in some embodiments.

The server 152 includes one or more processors 154 and one or morememory devices 158. The server 152 also may include, or be coupled to,one or more input devices 162. The server 152 includes one or morenetwork interface devices 170. The one or more processors 154, the oneor more memory devices 158, the one or more input devices 162 (sometimereferred to herein as “the input device 162” for brevity), the one ormore network interface devices 170 (sometime referred to herein as “thenetwork interface device 170” for brevity), etc., may be communicativelycoupled via one or more busses 174 (sometime referred to herein as “thebus 174” for brevity). In other embodiments, the server 152 may haveother suitable structures and/or components.

The one or more processors 154 (sometime referred to herein as “theprocessor 154” for brevity) may comprise one or more general purposeprocessors (e.g., a central processing unit), one or more specialpurpose processors (e.g., a co-processor, a graphics processor, etc.).At least one of the one or more processors 154 executes machine readableinstructions stored in the memory 158. The one or more memory devices158 (sometime referred to herein as “the memory 158” for brevity)include one or more of random access memory (RAM), read only memory(ROM), a FLASH memory, a magnetic disk drive, an optical disk drive,etc.

The one more input devices 162 include one or more suitable inputdevices such as a keyboard, a key pad, a mouse, a trackball, one or morebuttons, a touch screen that overlays a display device, etc. The one ormore network interface devices 170 comprise one or more suitable NICssuch as a wired network NIC, a wireless network NIC, etc. The server 152is communicatively coupled to the computer 102 and other computers (notshown) via the communication network 150. The server 152 may becommunicatively coupled to other cloud servers (not shown) via anothernetwork (not shown) and/or the network 150, in various embodiments.

Additionally, in some embodiments, the server 152 may be communicativelycoupled to a cloud storage database system 180, which may comprise oneor more suitable databases. The cloud storage database system 180 storesobjects (e.g., cloud storage objects) 184 that are accessible, via theserver 152 or another server, to computers (e.g., the computer 102) viathe network 150.

In an embodiment, the memory 158 may store a cloud-based developmentsystem 188. In various embodiments, the cloud-based development system188 is configured to interface with the cloud storage front end 144 tocreate cloud storage objects 184 in the cloud storage database 180, tomodify cloud storage objects 184, and/or to make cloud storage objects184 in the cloud storage database 180 accessible to computers via thenetwork 150. In some embodiments, the cloud-based development system 188includes a cloud storage management module 190 that is configured tointerface with the cloud storage front end 144 to create cloud storageobjects 184 in the cloud storage database 180, to modify cloud storageobjects 184, and/or to make cloud storage objects 184 in the cloudstorage database 180 accessible to computers via the network 150. Insome embodiments, the cloud storage management module 190 is astandalone module separate from the cloud-based development system 188.In some embodiments, the cloud storage management module 190 is acomponent of a system different than the cloud-based development system188. In some embodiments, the cloud-based development system 188 may beomitted.

In some embodiments, the computational application 140 is implemented asa kernel running on the server 152 and a front end running on thecomputer 102. In such embodiments, the cloud-based development system188 includes the kernel. In some embodiments, the computationalapplication 140 is included in the cloud-based development system 188and the computer 102 runs a thin client such as a web browser. In someembodiments, aspects of the computational application 140 running on theserver 152 (e.g., the kernel) are separate from the cloud-baseddevelopment system 188. In some embodiments, the cloud-based developmentsystem 188 is configured as described in U.S. patent application Ser.No. 14/549,541, filed Nov. 20, 2014, which is hereby incorporated byreference herein.

In some embodiments, the server 152 may be communicatively coupled to ananswering system and/or natural language processing system 194(hereinafter “answering system 190”) such as described in U.S. Pat. No.8,589,869 and/or U.S. patent application Ser. No. 13/678,168, filed Nov.15, 2012, which are hereby incorporated by reference herein in theirentireties. In some embodiments, the cloud-based development system 188may interface with the answering system 194 and utilize natural languageprocessing capabilities of the answering system 194 to process userinput, for example. In some embodiments, the cloud storage managementmodule 190 may interface with the answering system 194 and utilizenatural language processing capabilities of the answering system 194 toprocess user input, for example. In some embodiments, the server 152 maybe communicatively coupled to the answering system 194 via the network150 or another suitable communication network separate from the network150.

In some embodiments, the server 152 utilizes virtualization techniques.

In some embodiments, the system 100 includes a sensor device 198communicatively coupled to the network 150. The sensor device 198includes one or more sensors for measuring real world physicalparameters such as temperature, pressure, sound, motion, light, speed,acceleration, geographic position, physical orientation, etc. In variousembodiments, the sensor device 194 may be a standalone device, or may beincluded in another device or system such as a still photo camera, avideo camera, a security system, an air conditioning/heating controlsystem, etc.

The sensor device 198 also includes one or more processors and one ormore memories coupled to one or more busses (not shown), and has astructure generally similar to the computer 102, but having one or moresensors coupled to the bus(ses) and optionally omitting one or morecomponents of the computer 102, such as a display and/or an inputdevice.

In some embodiments, a memory of the sensor device may store areduced-size version of the computational application 140, e.g., withless functionality than the full-size computational application 140. Insome embodiments, however, the computational application 140 is omittedand the memory of the sensor device stores the cloud storage front end144 as a standalone application and/or module. In some embodiments, thecloud storage front end 144 is incorporated into another suitableapplication different than the computational application 140. In someembodiments, the cloud storage front end 144 is a web browser, and thesensor device 198 can cause the cloud server system to modify cloudstorage objects via the web browser. In some embodiments, the cloudstorage front end 144 is a communication application (e.g., an emailapplication, a text messaging application, etc.), and the sensor device198 can cause the cloud server system to modify cloud storage objectsvia the communication application, as will be discussed in more detailbelow.

In various embodiments, a user can utilize the cloud storage front end144 to cause the cloud storage management module 190 to create cloudstorage objects 184 and/or to cause the cloud storage management module190 to modify cloud storage objects 184. For example, in someembodiments, the computational application 140 implements a notebook, aspreadsheet, program, etc., that creates, in cooperation with the cloudstorage management module 190, cloud objects 184. As another example, insome embodiments, the computational application 140 implements adocument, a notebook, a spreadsheet, a program, etc., that modifies, incooperation with the cloud storage management module 190, cloud storageobjects 184. As another example, in some embodiments, the computationalapplication 140 implements a document, a notebook, a spreadsheet, aprogram, etc., that retrieves, in cooperation with the cloud storagemanagement module 190, data from cloud storage objects 184.

In embodiments that include a sensor device 198, a cloud storage frontend module 144 implemented in sensor device 198 modifies, in cooperationwith the cloud storage management module 190, cloud storage objects 184.For example, the cloud storage front end module 144 implemented insensor device 198 adds, in cooperation with the cloud storage managementmodule 190, sensor data (e.g., measured real world physical parameters)to already created cloud storage objects 184, according to anembodiment. Then, a user can process the sensor data using thecomputation application 140 implemented on the computer 102, in anembodiment. For example, the cloud storage front end module 144implemented on the computer 102 retrieves sensor data from the cloudstorage objects 184 and the computation application 140 implemented onthe computer 102 processes the sensor data, according to an embodiment.In some embodiments that include a sensor device 198, the cloud storagefront end module 144 implemented in sensor device 198 may be configuredto create, in cooperation with the cloud storage management module 190,cloud storage objects 184. In some embodiments that include a sensordevice 198, the cloud storage front end module 144 implemented in sensordevice 198 may be configured to retrieve, in cooperation with the cloudstorage management module 190, data from cloud storage objects 184.

Creating Cloud Storage Objects

In some embodiments, the computational application 140 provides abuilt-in function for creating cloud storage objects 184. A cloudstorage object 184 may be referred to as a “databin”, and thecomputational application 140 may provide a built-in function with adescriptive keyword such as “CreateDatabin”, where the built-in functionis for creating cloud storage objects 184 (e.g., databins). Thus, insome embodiments, a user can utilize the computational application 140and the CreateDatabin function to create cloud storage objects 184(“databins”). For example, in an embodiment, in response to a userentering the built-in function CreateDatabin into a workspace such as anotebook and causing the computational application 140 to evaluate thebuilt-in function (e.g., by pressing “Enter” or taking some othersuitable action), the computational application 140 interacts with thecloud storage management module 190, causing the cloud storagemanagement module 190 to create a databin. For example, thecomputational application 140 may evaluate the CreateDatabin functionentered within the workspace, and, responsive to the evaluation, use anapplication programming interface (API) to cause the cloud storagemanagement module 190 to create a databin. (Merely for ease ofexplanation and brevity, examples are discussed below in the context ofdatabins and built-in functions of the computational application 140 tocreate, modify, and access databins. In other embodiments, however,cloud storage objects 184 need not be databins or referred to as“databins”, and other suitable built-in functions of the computationalapplication 140 may be utilized to create, modify, and access cloudstorage objects 184.)

Responsive to receiving information from the cloud storage front end 144indicating that the user seeks to create a databin (e.g., via an API),the cloud storage management module 190 creates a databin and assignsthe created databin with a unique identifier (ID) to facilitate accessto the created databin. In an embodiment, the cloud storage managementmodule 190 randomly or pseudo-randomly generates the unique ID andassociates the unique ID with the created databin. In an embodiment, thecloud storage management module 190 associates a location of the createddatabin in the cloud storage 180 with the unique ID so that the databincan be accessed using the unique ID.

In some embodiments, the CreateDatabin function includes one or morearguments that a user can utilize to control characteristics of thedatabin. For example, an argument or arguments may be utilized tocontrol access permissions for the databin, in an embodiment. Forinstance, an argument of the CreateDatabin function may be utilized tocontrol whether the databin is publicly accessible via a public networksuch as the Internet. For example, the argument may provide options suchas (i) the databin is publicly accessible via the Internet; (ii) thedatabin is not accessible via a public network such as the Internet, butis accessible via a private network or system (e.g., a network or systemthat requires authentication (e.g., a login), a specific LAN, a specificWLAN, etc.); (iii) the databin is publicly accessible via the Internet,but can be accessed only by specific users; etc. In an embodiment,private access corresponds to access by an authorized user logged intothe system 100, i.e., someone who is not logged in cannot access adatabin configured for private access. In some embodiments, accesspermissions for a type of access may include options such as read onlyaccess, write only access, or read/write access, where the type ofaccess may be, for example, (i) public access via the Internet; (ii)access via a private network or system; etc. As an illustrative example,public access via the Internet may be limited to read-only access,whereas read/write access may be allowed via a private network orsystem.

As another example, an argument or arguments may be utilized to controlaccess permissions for specific users or machines, in an embodiment. Forinstance, the specific users may be identified using unique user IDs. Insome embodiments, access permissions for a specific user may includeoptions such as read only access, write only access, or read/writeaccess. As another example, specific machines may be identified usingunique IDs such as a universally unique ID (UUID) such as or including amedia access control (MAC) address assigned to a machine by amanufacturer or supplier. In some embodiments, access permissions for aspecific user may include options such as read only access, write onlyaccess, or read/write access.

In some embodiments, an argument or arguments of the CreateDatabinfunction may be utilized to indicate how data added to a databin shouldbe interpreted by the computational application 140 and/or how raw dataadded to the data bin should be converted to data type formatsrecognized by the computational application 140. For example, in anembodiment, the computational application 140 is configured to processvarious different types of data, and argument or arguments of theCreateDatabin function are utilized to indicate to the computationalapplication 140 the type or types of data in the databin. As anotherexample, in an embodiment, argument or arguments of the CreateDatabinfunction are utilized to indicate to the cloud storage management module190 how raw data added to the data bin should be converted to data typeformats recognized by the computational application 140.

In some embodiments, the cloud storage management module 190 may beconfigured to automatically determine how raw data in the data binshould be converted to data type formats recognized by the computationalapplication using techniques such as described in U.S. patentapplication Ser. No. 13/763,568, filed Feb. 8, 2013 and/or U.S. patentapplication Ser. No. 14/216,461, filed Mar. 17, 2014, both of which arehereby incorporated by reference herein in their entireties.

In some embodiments, with the computational application 140, any type ofdata is internally represented as a symbolic expression, with all morespecific data types treated as special cases—symbols to which additionalrules apply. In some embodiments, evaluation of a symbolic expression bythe computational application 140 involves applying to the symbolicexpression all transformation rules that fit that type of expression.For example, the computational application 140 will apply differenttransformation rules to numeric data versus text versus image data, etc.Thus, in an embodiment, an argument or arguments of the CreateDatabinfunction are utilized to indicate to the cloud storage management module190 how raw data added to the data bin should be converted to a symbolicformat recognized by the computational application 140.

In some embodiments, an argument or arguments of the CreateDatabinfunction may be utilized to indicate a function that should be invoked,e.g., by the computational application 140, when data is added to adatabin. For example, in an illustrative embodiment, the argument orarguments may specify that the computational application 140 is toinvoke a particular function that processes data added to a databin, andthen store a result of the invoked function in the databin.

In some embodiments, a set of arguments/options, such as describedabove, may be defined by the user for a class of databins. In suchembodiments, an argument of the CreateDatabin function may be utilizedto indicate the class of databin to be created, and then allarguments/options defined for that class will be applied to the createddatabin by the cloud storage management module 190. For example, in anembodiment, a user may define one or more of (i) access permissions forthe class, (ii) how data added to databins of the class should beinterpreted by the computational application 140 and/or how raw dataadded to databins of the class should be converted to data type formatsrecognized by the computational application 140, (iii) what function orfunctions should be invoked when data is added databins of the class,etc. When a user creates a databin specifying the particular class, thecloud storage management module 190 applies the specifiedarguments/options of the class to the created databin, and/or createsthe databin according to the specified arguments/options of the class.

In an illustrative embodiment, the CreateDatabin has a format asfollows:

-   -   CreateDatabin[ ]; and/or    -   CreateDatabin[options], where options is an argument or        arguments.

The argument(s) options may include:

-   -   “Name”—indicates a name to assign to the databin to be created;    -   “Class”—indicates the class of the databin to be created;    -   “Interpretation”—indicates how data entries to the databin are        to be interpreted;    -   “NewEntryFunction”—indicates a function to be applied when a new        entry is added to the databin; and/or    -   “Permissions”—indicates access permissions for the databin.

In an embodiment, after the cloud storage management module 190 createsthe databin, the cloud storage management module 190 returns an ID forthe databin (e.g., a UUID, a shortened version of the UUID, etc.) to thecloud storage front end 144 (e.g., via an API). Thus, in an embodiment,responsive to evaluation of the CreateDatabin function in a workspace(e.g., a notebook), the computational application 140 displays and/ormakes available the returned ID in the workspace. In an embodiment inwhich the computational application 140 is configured to internallyrepresent different types of data as symbolic expressions, databinsthemselves are represented as symbolic expressions. Thus, in anembodiment, responsive to evaluation of the CreateDatabin function in aworkspace (e.g., a notebook), the computational application 140 returnsa handle to the symbolic databin object, which may include the ID of thedatabin.

FIG. 2A is an example in which a programmer utilizes the CreateDatabinfunction to create a databin in the cloud storage 180 (FIG. 1),according to an embodiment. The programmer has entered into a notebookan expression bin=CreateDatabin[ ]. The computational application 140evaluates the entered expression and, in response, utilizes an API tocause the cloud storage management module 190 to create a databin. Next,the cloud storage management module 190 creates the databin and returnsa handle to the created symbolic databin object. The databin objectindicates a corresponding short ID for the databin. The computationalapplication 140 sets the variable “bin” equal to the handle to thecreated symbolic databin object.

FIG. 2B is another example in which a programmer utilizes theCreateDatabin function to create a databin in the cloud storage 180(FIG. 1), according to an embodiment. The programmer has entered into anotebook an expressionbin=CreateDatabin[“Interpretation”->{“city”->“City”,“temp”->Restricted[“StructuredQuantity”, “DegreesCelsius”]}]. Thecomputational application 140 evaluates the entered expression and, inresponse, utilizes an API to cause the cloud storage management module190 to create a databin.

In the example of FIG. 2B, the programmer uses parameters to specify howraw data added to the databin should be converted to data type formatsrecognized by the computational application 140. For example, entriesassociated with a key “city” should be converted to City symbolicobjects, which are stored in a format recognized by the computationalapplication 140 as city entities. Also, entries associated with a key“temp” should be converted to symbolic objects that are stored in aformat recognized by the computational application 140 as temperaturevalues with units of Celsius.

Also in the example of FIG. 2B, the programmer uses parameters tospecify a function to be applied when raw data is added to the databin.For example, for entries associated with the key “temp”, the function“Restricted” is to be applied, where Restricted is a built-in functionof the computational application 140. The Restricted function as setforth in FIG. 2B will convert raw data entries to symbolicallyrepresented temperature values with units of Celsius. Additionally, theRestricted function as set forth in FIG. 2B will generate an errormessage when the raw data value does not corresponds to a temperaturevalue with units of Celsius. For example, if the entry is “temp”->xxxx,an error message will be generated because the raw data entry xxxxcannot be converted to a temperature value with units of Celsius.

The cloud storage management module 190 creates the databin and returnsa handle to the created symbolic databin object. The computationalapplication 140 sets the variable “bin” equal to the handle to thecreated symbolic databin object.

In the example of FIG. 2B, the value of the Interpretation parameterspecifies a data signature for the created databin, where the datasignature specifies how entries in the databin are to be interpreted bythe computational application 140, according to an embodiment. Forinstance, in the example of FIG. 2B, the data signature specifies thatentries associated with the key “city” are to be interpreted as Cityentities, and entries associated with the key “temp” are to beinterpreted as temperature values with units of degrees Celsius.Specifying how entries in the databin are to be interpreted by thecomputational application 140 may be referred to as specifying datasemantics.

FIG. 2C is another example in which a programmer utilizes theCreateDatabin function to create a databin in the cloud storage 180(FIG. 1), according to an embodiment. In the example of FIG. 2C, theparameter “Name” is utilized to assign a name (e.g., “My new data bin”)to the created databin. The cloud storage management module 190 createsthe databin and returns a handle to the created symbolic databin object.The computational application 140 sets the variable “bin” equal to thehandle to the created symbolic databin object.

FIG. 2D is another example in which a programmer utilizes theCreateDatabin function to create a databin in the cloud storage 180(FIG. 1), according to an embodiment. In the example of FIG. 2D, theparameter “Permissions” is utilized to make the created databinaccessible only to those logged into the cloud-based development system188 by setting the Permissions parameter to a value “Private”. The cloudstorage management module 190 creates the databin and returns a handleto the created symbolic databin object. The computational application140 sets the variable “bin” equal to the handle to the created symbolicdatabin object.

In some embodiments, databins can be created additionally oralternatively using other suitable techniques. For example, in someembodiments, a databin can be created using a graphical user interface(GUI) implemented by the computer 102 (FIG. 1), where the GUI utilizesone or more suitable GUI mechanisms, such as one or more of i) one ormore buttons, ii) one or more hypertext links, iii) one or morepull-down menus, iv) one or more pop-up menus, v) one or more textboxes, etc. Referring again to FIG. 1, in an embodiment, in response toa selecting to create a databin with the GUI, the computer 102 interactswith the cloud storage management module 190, causing the cloud storagemanagement module 190 to create a databin. For instance, the GUI may beimplemented using a web browser application executed by the computer102, in an embodiment. As another example, the GUI may be implementedusing a mobile application (mobile app) executed by the computer 102, inan embodiment. In embodiments in which the GUI is implemented using aweb browser application, the server 152 (or another servercommunicatively coupled to the server 152) may implement a web servermodule (not shown in FIG. 1) that serves web pages to the web browserapplication on the computer 102, and the web pages may provide one ormore GUI mechanisms such as described above.

Responsive to receiving information from the computer 102 indicatingthat the user seeks to create a databin (e.g., via an API), the cloudstorage management module 190 creates a databin and assigns the createddatabin with an ID to facilitate access to the created databin andassociates a location of the created databin in the cloud storage 180with the unique ID so that the databin can be accessed using the uniqueID as discussed above, according to an embodiment.

In some embodiments, the user can utilize one or more GUI mechanisms tocontrol characteristics of the databin, such as access permissions, howdata added to a databin should be interpreted by the computationalapplication 140 and/or how raw data added to the data bin should beconverted to data type formats recognized by the computationalapplication 140, to indicate a function that should be invoked, e.g., bythe computational application 140, when data is added to a databin, etc.In an illustrative embodiment, the user can utilize one or more GUImechanisms to control characteristics of the databin, such as one of, orany suitable combination of two or more of: a name to assign to thedatabin, a class of the databin, how data entries to the databin are tobe interpreted, a function to be applied when a new entry is added tothe databin, access permissions for the databin, etc.

In an embodiment, after the cloud storage management module 190 createsthe databin, the cloud storage management module 190 returns an ID forthe databin (e.g., a UUID, a shortened version of the UUID, etc.) to thecomputer 102 (e.g., via an API), and the ID is displayed on a displaydevice of the computer 102 by the web browser, the mobile app, etc.

The created databin may comprise one or more files. For example, in oneembodiment, the databin includes one or more metadata files and one ormore data files for storing data subsequently added to the databin. Insome embodiments, the databin may be organized as a file system (e.g., adirectory), and creation of the databin may include creating the filesystem (e.g., the directory). In some embodiments, a file or files ofthe databin may be a text file(s) written in a suitable markup languagesuch as the Extensible Markup Language (XML), an XML-based language, aproprietary markup language, etc. Thus, creation of the databin mayinclude creating one or more files written in a suitable markuplanguage, according to some embodiments.

FIG. 3 is an illustrative example of a directory 300 created for adatabin, according to an illustrative embodiment. Thus, in someembodiments, creating a databin comprises creating a suitable directorysuch as the directory 300. In some embodiments, however, some of thefolders, files, etc., illustrated in FIG. 3 are not created upon initialcreation of a databin, but rather are subsequently created when thedatabin is modified by adding data to the databin, when data is readfrom the databin, etc., for example. The directory 300 is stored in thecloud storage 180 (FIG. 1), in an embodiment.

The directory 300 includes a top level folder 304. In some embodiments,the top level folder 304 may be named or otherwise associated with an ID(e.g., a UUID) associated with the databin to facilitate access to thetop level folder 304 using the ID. The top level folder 304 includes asubfolder 308, which in turn includes a file 312 for storing data addedto the databin. The top level folder 304 also includes a subfolder 316,which in turn includes a plurality of files 320, 324, 328 that areutilized for storing information that indicates, and/or facilitatescalculating, usage information associated with the databin, such as oneor more of i) a volume of data stored in the databin, a rate of addingdata to the databin, etc.

The top level folder 304 also includes a file 332 for storing metadataregarding the databin, and a file 336 for storing information indicatinghow data in the subfolder 308 are to be interpreted by the computationalapplication 140 and/or how raw data in the subfolder 308 are to beconverted to data type formats recognized by the computationalapplication 140 (e.g., semantic information). The top level folder 304further includes a file 340 for storing information that indicates,and/or facilitates calculating, usage information associated with thedatabin, such as a rate of acquiring data from the databin, etc.

In an embodiment, responsive to receiving information from the computer102 indicating that the user seeks to create a databin (e.g., via anAPI), the cloud storage management module 190 creates a directory, suchas the directory 300, or at least some of the directory. For example, inan embodiment, responsive to receiving information from the computer 102indicating that the user seeks to create a databin (e.g., via an API),the cloud storage management module 190 creates at least some of thefolders and/or at least some of the files illustrated in FIG. 3.

As an illustrative example, the file 332 includes the following metadatainformation set forth using a markup language, according to anillustrative embodiment:

<|“Bin” −> <|“UUID” −> “EE56f7165fefd-dd74-40a3-b901- 7ad9115f8ebe”, “Name” −> “Unnamed”|>, “ReadAuthorization” −> <|“Type” −> “Public”|>,“WriteAuthorization” −> <|“Type” −> “Public”|>, “Owner” −>“johnsmith@wolfram.com”, “OwnerUUID” −>“56ee39ac-323d-481b-a9e4-6df0dd549816”, “Administrators” −>{“johnsmith@wolfram.com”}, “Interpretation” −> {“n” −> “Number”, “x” −>“Country”}, “DataFormatVersion” −> 2, “CreationDate” −>DateObject[{2015, 5, 28}, TimeObject[{18, 54, 49.96018}, TimeZone −>0.], “Creator” −> “johnsmith@wolfram.com”|>

In this embodiment, the metadata file 332 includes: a markup “bin”associated with content corresponding to a UID (e.g., UUIDEE56f7165fefd-dd74-40a3-b901-7ad9115f8ebe) assigned to the databin; amarkup “Name” associated with content indicating a name assigned to thedatabin or that the databin is unnamed (e.g., “Unnamed”); a markup“ReadAuthorization” associated with content that specifies read accessrights for the databin (e.g., “Public”, “Private”, etc.); a markup“WriteAuthorization” associated with content that specifies write accessrights for the databin (e.g., “Public”, “Private”, etc.); a markup“Owner” associated with content that specifies an ID corresponding to auser account associated with the databin (e.g., a username such as anemail address); a markup “OwnerUUID” associated with content thatspecifies a unique ID associated with the user account (e.g., a UUID); amarkup “Administrators” associated with content that specifies one ormore users that have administrative privileges with regard to thedatabin (e.g., one or more usernames such as an email addresses); amarkup “Interpretation” associated with content that specifies how thecomputational application 140 is to interpret data stored to the databin(e.g., including an association between a key (e.g., “x”) andspecification data regarding how to interpret data corresponding to thekey (e.g., “Country”); a markup “DataFormatVersion” associated withcontent that specifies version information regarding a data formatassociate with the databin; a markup “CreationDate” associated withcontent that specifies when the databin was created; and a markup“Creator” associated with content that specifies an ID corresponding toa user that created the databin (e.g., a username such as an emailaddress).

In other embodiments, the metadata file 332 omits some of theinformation discussed above and/or includes additional suitableinformation. For example, in some embodiments, when the databin isassociated with the sensor device 198, the metadata file 332 (or anotherfile in the directory 300) includes identifying data corresponding tothe sensor device 198, such as one or more of a serial number, a UUID, aunique user ID corresponding to the sensor device 198, etc., assigned tothe sensor device 198 by a manufacturer, distributer, etc., of thesensor device 198.

In some embodiments, another suitable markup language is utilized suchas XML, an XML-based language, etc.

In an embodiment, responsive to receiving information from the computer102 indicating that the user seeks to create a databin (e.g., via anAPI), the cloud storage management module 190 creates the file 332.

As another illustrative example, the file 336 includes the information,set forth using a markup language, that indicates how raw data in thefile 312 are to be converted to data type formats recognized by thecomputational application 140, according to an illustrative embodiment:

-   -   FormObject[<|“n”-> <|“Interpreter”->“Number”|>, “x”->        <|“Interpreter”->“Country”|>|>]

In this embodiment, the file 336 includes a structured statementincluding keywords corresponding to built-in functions of thecomputational application 140 (e.g., “FormObject”, “Interpreter”), andkeywords corresponding to parameters of the built-in functions (e.g.,“Number”, “Country”). The structured statement, when evaluated by thecloud storage management module 190, instructs the cloud storagemanagement module 190 how to convert raw data in the file 312 to datatype formats recognized by the computational application 140. In theillustrative example above, the structured statement, when evaluated bythe cloud storage management module 190, instructs the cloud storagemanagement module 190 to convert raw data associated with the key “n” toa data type “Number”, and to convert data associated with the key “x” toa data type “Country”.

In an embodiment, responsive to receiving information from the computer102 indicating that the user seeks to create a databin (e.g., via anAPI), the cloud storage management module 190 creates the file 336.

In an embodiment, responsive to receiving information from the computer102 indicating that the user seeks to create a databin (e.g., via anAPI), the cloud storage management module 190 creates the file 312 as anempty file.

FIG. 4 is a flow diagram of an example method 400 for creating adatabin, according to an embodiment. The method 400 may be implementedin the system 100 of FIG. 1, in an embodiment, and the method 400 isdescribed with reference to the system 100 of FIG. 1 for explanatorypurposes. In other embodiments, however, the method 400 is implementedin another suitable system. Similarly, in some embodiments, anothersuitable method different than the method 400 is implemented in thesystem 100.

At block 404, programmer input corresponding to a built-in function ofthe computational application 140 is received, where the built-infunction is for creating databins. In an embodiment, the programmerinput may include i) a keyword (e.g., CreateDatabin) corresponding tothe built-in function, and ii) optionally, one or more parameters of thebuilt-in function such as described above. The programmer input may bereceived via one or more user input devices of the computer 102, andinput into a document such as a notebook, a spreadsheet, etc.

At block 408, the programmer input is evaluated by the computationalapplication 140, and, responsive to the evaluation, one or more APIcalls may be generated by the cloud storage front end module 144, wherethe one or more API calls correspond to requests for a databin to becreated, and the one or more API calls optionally may includeindication(s) of one or more parameters such as described above.

The one or more API calls may be transmitted from the computer 102 tothe server 152 via the network 150. At block 412, the API call(s) arereceived by the server 152.

At block 416, the one or more API calls are evaluated by the cloudstorage management module 190, and, responsive to the evaluation, adatabin is created at block 420. Creating the databin may includecreating a file system (e.g., a directory) having one or files, such asdescribed above. For example, creating the databin may include creatingone or more files written in a suitable markup language such asdescribed above, according to some embodiments.

Creating the databin may include generating an ID (e.g., a UUID) andassociating the ID with the databin. The ID may be utilized subsequentlyto access the created databin. At block 424, the cloud storagemanagement module 190 may return the ID to the cloud storage front endmodule 144 according to an API. For example, the ID may be transmittedby the server 152 to the computer 102 via the network 150, in anembodiment.

In various other embodiments, one or more blocks of the method 400 maybe omitted, blocks may be rearranged, one or more additional blocks maybe added, etc.

Referring again to FIG. 1, in some embodiments, the cloud storagemanagement module 190 may be implemented as a multi-threaded servermodule to handle high volume and/or high rate accesses to cloud storageobjects 184. For example, different threads may handle differentrequests to create databins, in an embodiment.

Adding Data to Cloud Storage Objects

Referring again to FIG. 1, in some embodiments, the system 100 providesa plurality of mechanisms for adding data to databins using techniquessuch as described above (or using other suitable techniques). In suchembodiments, the plurality of available mechanisms for adding data todatabins may provide much flexibility for users to gather data forsubsequent analysis by the computational application 140 (and/or aseparate data analysis application). For example, in an illustrativeembodiment, data can be added to a databin i) programmatically via afunction in a notebook being evaluated by the computational application140, ii) via a universal resource locator (URL), iii) via one or moreweb pages served by a web server module implemented by the server 152(or another server coupled to the server 152), iv) via email, v)directly by the sensor device 198, etc.

In other embodiments, the system only provides one of, or a subset of,the mechanisms for adding data to databins discussed above, and/orprovides one or more other suitable mechanisms.

Adding Data Programmatically

In some embodiments, the computational application 140 provides abuilt-in function for adding data to databins. For example, thecomputational application 140 may provide a built-in function with adescriptive keyword such as “DatabinAdd”, where the built-in function isfor adding data to cloud storage objects 184 (e.g., databins). Thus, insome embodiments, a user can utilize the computational application 140and the DatabinAdd function to add data to cloud storage objects 184(“databins”). For example, in an embodiment, in response to a userentering the built-in function DatabinAdd into a workspace such as anotebook and causing the computational application 140 to evaluate thebuilt-in function (e.g., by pressing “Enter” or taking some othersuitable action), the computational application 140 interacts with thecloud storage management module 190, causing the cloud storagemanagement module 190 to add data to a specified databin. For example,the computational application 140 may evaluate the DatabinAdd functionentered within the workspace, where parameters of the DatabinAddfunction specify i) a particular databin and ii) data to be added to thespecified databin, and, responsive to the evaluation, use an API tocause the cloud storage management module 190 to add the specified datato the specified databin. In some embodiments, evaluation of theDatabinAdd function involves creating a connection (e.g., a transmissioncontrol protocol (TCP) connection, a stream control transmissionprotocol (SCTP) connection, etc.) between a socket corresponding to thecloud storage front end 144 and a socket corresponding to the specifieddatabin. Thus, in such embodiments, when the connection has already beenestablished, evaluation of the DatabinAdd function may involve sendingthe data to the already established connection. For example, in anembodiment, when the connection has already been established, evaluationof the DatabinAdd function may involve sending the data to the socketcorresponding to the cloud storage front end 144.

Responsive to receiving information from the cloud storage front end 144indicating that the user seeks to add specified data to a specifieddatabin (e.g., via an API, via an established connection), the cloudstorage management module 190 stores the specified data in the databin.In some embodiments, the cloud storage front end 144 first locates thespecified data bin in the cloud storage 180.

In some embodiments, the DatabinAdd function includes arguments that auser can utilize to specify i) a databin, and ii) data to be added tothe databin. In an illustrative embodiment, the DatabinAdd function hasa format as follows:

-   -   DatabinAdd[bin, data], where bin is an argument specifying a        unique ID associated with a databin, and data is an argument or        arguments specifying data to be added to the databin.

FIG. 5A is an example in which a programmer utilizes the DatabinAddfunction to add data to a databin in the cloud storage 180 (FIG. 1),according to an embodiment. The example of FIG. 5A corresponds to addingdata to a databin created as described in the example of FIG. 2A. Theprogrammer has entered into a notebook an expression DatabinAdd[bin,1234], where the variable “bin” is set to the handle to the symbolicdatabin object created in the example of FIG. 2A. The computationalapplication 140 evaluates the entered expression and, in response,utilizes an API, a connection, etc., to cause the cloud storagemanagement module 190 to add the data “1234” to the databincorresponding to value of the variable “bin”. Next, the cloud storagemanagement module 190 adds the data to the specified databin and returnsa handle to the specified databin.

FIG. 5B is another example in which a programmer utilizes the DatabinAddfunction to add data to a databin in the cloud storage 180 (FIG. 1),according to an embodiment. The example of FIG. 5B corresponds to addingdata to a databin created as described in the example of FIG. 2B. Theprogrammer has entered into a notebook an expression Databin[bin,<|“city”->“nyc”, “temp”->20.4|>], where the variable “bin” is set to thehandle to the symbolic databin object created in the example of FIG. 2B.The computational application 140 evaluates the entered expression and,in response, utilizes an API, a connection, etc., to cause the cloudstorage management module 190 to add the data “nyc”, associated with thekey “city”, and the data 20.4, associated with the key “temp”, to thedatabin corresponding to value of the variable “bin”. Next, the cloudstorage management module 190 adds the data to the specified databin andreturns a handle to the specified databin.

As discussed above in connection with the example of FIG. 2B, it wasspecified that entries associated with a key “city” should be convertedto City symbolic objects, which are stored in a format recognized by thecomputational application 140 as city entities, and entries associatedwith a key “temp” should be converted to symbolic objects that arestored in a format recognized by the computational application 140 astemperature values with units of Celsius. Thus, the cloud storagemanagement module 190 recognizes that the data “nyc” in FIG. 5 isassociated with the key “city”, and the data 20.4 is associated with thekey “temp”. Thus, the cloud storage management module 190 will determinethat the raw data “nyc” corresponds to New York City, and will convertthe raw data “nyc” to a symbolic object corresponding to the entity NewYork City. Similarly, the cloud storage management module 190 willconvert the raw data “20.4” to a symbolic object corresponding to atemperature of 20.4 degrees in units of Celsius.

In an embodiment, data is stored to the databin as raw data, and the rawdata is also converted to appropriate data types recognized by thecomputational application 140 and then stored to the databin. In anotherembodiment, when the converted data has been stored to the databin, theraw data is deleted from the databin. In other embodiments, the raw datais not stored to the databin, but rather the raw data is first convertedto appropriate data types recognized by the computational application140 and then the converted data is stored to the databin instead of theraw data.

In some embodiments, when data is stored to the databin, metadataregarding the data entry is also stored to the databin. For example, inan embodiment, a timestamp is stored to the databin, where the timestampindicates when the data was stored to the databin. As another example,in an embodiment, a UUID for the data entry is generated, and the UUIDis stored to the databin, where the UUID is associated with the dataentry. As another example, in an embodiment, a user ID is stored to thedatabin, where the user ID indicates a user requested the data to bestored to the databin. As another example, in an embodiment, locationdata (e.g., city/state, geoposition data (e.g., latitude/longitude, GPScoordinates, etc.)) is stored to the databin, where the location dataindicates where the request to store the data originated. For example,the location data may indicate a location of the user computer 102.

In an embodiment, responsive to receiving information from the computer102 indicating that specified data is to be added to a specified databin(e.g., via an API, a connection, etc.), the cloud storage managementmodule 190 locates a directory corresponding to the databin, such as thedirectory 300, using the ID provided via the API, information regardingthe connection, etc. For example, in an embodiment, responsive toreceiving information from the computer 102 indicating that specifieddata is to be added to a specified databin (e.g., via an API, aconnection), the cloud storage management module 190 accesses one ormore files in the directory, such one or more of the files illustratedin FIG. 3.

As an illustrative example, the cloud storage management module 190 maylocate the folder 308 and the file 312 within the folder 308, and thenmodify the file 312 to add the specified data to the file 312. Accordingto an illustrative embodiment that corresponds to the example of FIG.5B, the following text is added to the file 312:

<drop> Timestamp −> <::>  <TIMESTAMP><:>{2015, 5, 28, 18, 55,4.26938}<:>  <::> <:>UUID<:>“data29cc186c-48ba-4303-91ac-6f5058795bfa”<:> <:> Size<:>432<:><:> InterpretedQ<:>False<:> <:> SourceInformation<:><|“TimeRecorded” −>{2015, 5, 28, 18, 55, 4.26938{grave over ( )}8.38293978954441},“TimeGiven” −> Missing[ ], “Authenticated” −> True, “WolframID” −>“johnsmith@wolfram.com”, “GeoLocation” −> GeoPosition[{40.11, −88.24}],“SourceType” −> Missing[ ], “SourceDetails” −> <|“RequesterAddress” −>None, “Requester” −> “johnsmith@wolfram.com”, “UserAgent” −> None|>|><:><:> RawData<:><|“city” −> “nyc”, “x” −> “temp” −>20.4|><:>

In this embodiment, the file 312 is generated to include metadata suchas: timestamp data corresponding to the entry; a UUID corresponding tothe entry; size data corresponding to a size of the entry and/or a sizeof the databin; other metadata corresponding to one or more of i) a userthat requested entry of the data in the databin, ii) locationinformation corresponding to the request to add data to the entry, etc.The different metadata may be indicated and demarcated within the file312 with markups.

In an embodiment, the raw data is added. Additionally, in an embodiment,the metadata includes data that indicates whether the raw data has beenconverted to appropriate data types recognized by the computationalapplication 140. For example, a markup (e.g., InterpretedQ) andassociated data (e.g., “False”) indicates whether the raw data has beenconverted to appropriate data types recognized by the computationalapplication 140. In the illustrative example, the associated data“False” indicates that the raw data has not yet been converted toappropriate data types recognized by the computational application 140.

In other embodiments, the file 312 omits some of the informationdiscussed above and/or includes additional suitable information. In someembodiments, another suitable markup language is utilized such as XML,an XML-based language, etc.

In an embodiment, if the file 312 has not yet been created, responsiveto receiving information from the computer 102 indicating that the userseeks to add data to the databin associated with the directory 300(e.g., via an API), the cloud storage management module 190 creates thefile 312.

In an embodiment, the cloud storage management module 190 includes a rawdata conversion module that analyzes databins to determine whether eachdatabin includes raw data that has not yet been converted to appropriatedata types recognized by the computational application 140. For example,in an embodiment, the raw data conversion module analyzes metadataassociated with a databin (e.g., in the file 312 or in another suitablelocation) to determine whether raw data in the databin has beenconverted to appropriate data types recognized by the computationalapplication 140. For example, in an embodiment, the raw data conversionmodule analyzes data associated with the markup InterpretedQ todetermine whether the data corresponds to “False” (which indicates thatthe raw data has not been converted to appropriate data types recognizedby the computational application 140) or to “True” (which indicates thatthe raw data has been converted to appropriate data types recognized bythe computational application 140). The raw data conversion module mayexecute as a background process and/or in response to a read access to adatabin, in some embodiments.

In an embodiment, when raw data is added to a databin, an indication ofthe databin (e.g., the ID of the databin) and, optionally, an indicationof the raw data in the databin (e.g., the ID of the entry), is stored ina queue associated with the raw data conversion module. In anembodiment, the raw data conversion module examines the queue todetermine databins that include raw data that has not been converted toappropriate data types recognized by the computational application 140.

Responsive to determining that a databin includes raw data that has notyet been converted to appropriate data types recognized by thecomputational application 140, the raw data conversion module mayutilize information in the metadata file 332 and/or the file 336 thatspecifies how the raw data is to be converted and/or processed. Forexample, in an embodiment, the raw data conversion module may utilizeinformation in the file 336 to process the raw data. When the raw datahas been converted, the raw data conversion module may store theconverted data in the databin, e.g., in the file 312. Continuing withthe illustrative above, the file 312 may be modified so that markup dataindicating the converted data in a format recognized by thecomputational application 140:

Data −> <::>  <VALUE><:>city<:>Entity[“City”, “New York City”]<:>  <::> <VALUE><:>x<:> Quantity[20.4, “Celsius”]<:>  <::>is included in the file 312:

<drop> Data −> <::>  <VALUE><:>city<:>Entity[“City”, “New York City”]<:> <::>  <VALUE><:>x<:> Quantity[20.4, “Celsius”]<:>  <::> <:>Timestamp −><::>   <TIMESTAMP><:>{2015, 5, 28, 18, 55, 4.26938}<:>   <::> <:>UUID<:>“data29cc186c-48ba-4303-91ac-6f5058795bfa”<:> <:> Size<:>432<:><:> InterpretedQ<:>False<:> <:> SourceInformation<:><|“TimeRecorded” −>{2015, 5, 28, 18, 55, 4.26938{grave over ( )}8.38293978954441},“TimeGiven” −> Missing[ ], “Authenticated” −> True, “WolframID” −>“johnsmith@wolfram.com”, “GeoLocation” −> GeoPosition[{40.11, −88.24}],“SourceType” −> Missing[ ], “SourceDetails” −> <|“RequesterAddress” −>None, “Requester” −> “johnsmith@wolfram.com”, “UserAgent” −> None|>|><:><:> RawData<:><|“city” −> “nyc”, “x” −> “temp” −>20.4|><:>

As another illustrative example, the file 336 includes the information,set forth using a markup language, that indicates how raw data in thefile 312 are to be converted to data type formats recognized by thecomputational application 140, according to an illustrative embodiment:

FormObject[<|“n” −> <|“Interpreter” −> “Number”|>,  “x” −><|“Interpreter” −> “Country”|>|>]

In this embodiment, the file 336 includes a structured statementincluding keywords corresponding to built-in functions of thecomputational application 140 and/or the cloud-based development system188 (e.g., “FormObject”, “Interpreter”), and keywords corresponding toparameters of the built-in functions (e.g., “Number”, “Country”). Thestructured statement, when evaluated by the cloud storage managementmodule 190, instructs the cloud storage management module 190 how toconvert raw data in the file 312 to data type formats recognized by thecomputational application 140. In the illustrative example above, thestructured statement, when evaluated by the cloud storage managementmodule 190, instructs the cloud storage management module 190 to convertraw data associated with the key “n” to a data type “Number”, and toconvert data associated with the key “x” to a data type “Country”.

In some embodiments, as discussed above, the programmer uses parametersto specify a function to be applied when raw data is added to thedatabin. In some embodiments, an indication of the function to beapplied is included in the structured statement stored in the file 336.The structured statement, when evaluated by the cloud storage managementmodule 190, instructs the cloud storage management module 190 how toapply the specified function.

In an embodiment, the file 336 indicates the data signature discussedabove.

In an embodiment, in response to the file 312 reaching a size threshold,a new file for storing data may be created, and subsequently receiveddata may be added to the new file. Similarly, as each additional filereaches the size threshold (or a different threshold), a further filemay be created. In some embodiments, a background process monitors thesize of files 312 for various databins and creates new files as needed.Data that associates or links the multiple data files may be stored inthe file system 300.

FIG. 6 is a flow diagram of an example method 600 for adding data to adatabin, according to an embodiment. The method 600 may be implementedin the system 100 of FIG. 1, in an embodiment, and the method 600 isdescribed with reference to the system 100 of FIG. 1 for explanatorypurposes. In other embodiments, however, the method 600 is implementedin another suitable system. Similarly, in some embodiments, anothersuitable method for adding data to databins different than the method600 is implemented in the system 100.

At block 604, programmer input corresponding to a built-in function ofthe computational application 140 is received, where the built-infunction is for adding data to databins. In an embodiment, theprogrammer input may include i) a keyword (e.g., DatabinAdd)corresponding to the built-in function, and ii) one or more parametersof the built-in function such as described above. For example, a firstparameter may indicate the databin and a second parameter may indicatedata to be added to the databin. The programmer input may be receivedvia one or more user input devices of the computer 102, and input into adocument such as a notebook, a spreadsheet, etc.

At block 608, the programmer input is evaluated by the computationalapplication 140, and, responsive to the evaluation, one or more APIcalls may be generated by the cloud storage front end module 144, wherethe one or more API calls correspond to requests for data to be added tothe specified databin, and the one or more API calls optionally mayinclude indication(s) of one or more parameters such as described above.In some embodiments, responsive to the evaluation, a connection (e.g., aTCP connection, an SCTP connection, etc.) between a socket correspondingto the cloud storage front end 144 and a socket corresponding to thespecified databin is created. In some embodiments, when the connectionhas already been established, evaluation of the DatabinAdd function mayinvolve sending the data to the already established connection. Forexample, in an embodiment, when the connection has already beenestablished, evaluation of the DatabinAdd function may involve sendingthe data to the socket corresponding to the cloud storage front end 144.

The one or more API calls may be transmitted from the computer 102 tothe server 152 via the network 150. At block 612, the API call(s) arereceived by the server 152. In some embodiments, block 612 is modifiedto include the server 152 establishing a connection (e.g., a TCPconnection, an SCTP connection, etc.). In some embodiments, when theconnection has already been established, block 612 is modified toinclude the server 152 receiving data via the connection.

At block 616, the one or more API calls are evaluated by the cloudstorage management module 190, and, responsive to the evaluation, thespecified raw data is added to the databin at block 620. Adding data tothe databin may include adding the raw data to a file such as the file312 using a suitable markup language such as described above, accordingto some embodiments. If the file 312 has not yet been created, block 620may include creating the file 312. In some embodiments, blocks 616 and620 are modified to include the server 152 receiving data via anestablished connection.

In some embodiments, in conjunction with adding raw data to the databin,the cloud storage management module 190 may update metadatacorresponding to the databin. For example, the cloud storage managementmodule 190 may add timestamp data to the databin and associate thetimestamp data with the added raw data, the timestamp corresponding to atime at which the raw data was received by the storage management module190 or corresponding to a time at which the raw data was stored in thedatabin by the storage management module 190. As another example, thecloud storage management module 190 may modify metadata that indicateshow much data is stored in the databin and/or a size of the databin.

At block 624, the cloud storage management module 190 may return an IDof the databin to the cloud storage front end module 144 according to anAPI. For example, the ID may be transmitted by the server 152 to thecomputer 102 via the network 150, in an embodiment. In some embodiments,the ID may be transmitted by the server 152 to the computer 102 via aconnection such as described above.

At block 628, the cloud storage management module 190 may convert theraw data to formatted data recognized by the computational applicationand store the formatted data in the databin. For example, information inthe metadata file 332 and/or the file 336 that specifies how the rawdata is to be converted and/or processed may be utilized to convert theraw data. For example, in an embodiment, the raw data conversion modulemay utilize information in the file 336 to process the raw data in thefile 312. When the raw data has been converted, the converted data maybe stored in the databin, e.g., in the file 312. Block 628 may beperformed responsive to determining that a databin includes raw datathat has not yet been converted to appropriate data types recognized bythe computational application 140, in an embodiment. Similarly, block628 may be performed responsive to i) an operation attempting to accessdata in the databin and ii) determining that the databin includes rawdata that has not yet been converted to appropriate data typesrecognized by the computational application 140, in an embodiment. Insome embodiments, block 628 may be performed as a background process.

In some embodiments, in conjunction with storing converted data to thedatabin, the cloud storage management module 190 may update metadatacorresponding to the databin. For example, the cloud storage managementmodule 190 may modify metadata that indicates how much data is stored inthe databin and/or a size of the databin.

In various other embodiments, one or more blocks of the method 600 maybe omitted, blocks may be rearranged, one or more additional blocks maybe added, etc. For example, in an embodiment, the raw data is not storedin the databin, and block 620 may be omitted. For example, conversion ofraw data and storage of the formatted data at block 628 may replaceblock 620 and be responsive to evaluation of the API call(s) or receiptof data via a connection (block 616). As another example, in anotherembodiment, block 624 is omitted or modified to return otherinformation, such as a UID of the data entry.

In some embodiments, when multiple requests to add data to a samedatabin (and/or when multiple requests to add data to differentdatabins) are received by the server 152 at a high rate, receivedrequests and/or raw data may be initially stored in one or more buffers.In an embodiment, buffered requests are later handled when the server152 has sufficient processing bandwidth and/or when the cloud storagememory system 180 has sufficient bandwidth. In an embodiment, bufferedraw data is stored in databin(s) when the server 152 has sufficientprocessing bandwidth and/or when the cloud storage memory system 180 hassufficient bandwidth. In some embodiments, handling buffered requestsand/or storing buffered raw data to databins may be performed asbackground processes.

Adding Data Via Web Page, App, Etc.

In some embodiments, data can be added to a databin using a GUIimplemented by the computer 102 (FIG. 1), where the GUI utilizes one ormore suitable GUI mechanisms, such as one or more of i) one or morebuttons, ii) one or more hypertext links, iii) one or more pull-downmenus, iv) one or more pop-up menus, v) one or more text boxes, etc.Referring again to FIG. 1, in an embodiment, in response to a selectingto add data to a databin with the GUI, the computer 102 interacts withthe cloud storage management module 190, causing the cloud storagemanagement module 190 to add data to the databin. For instance, the GUImay be implemented using a web browser application executed by thecomputer 102, in an embodiment. As another example, the GUI may beimplemented using a mobile application (mobile app) executed by thecomputer 102, in an embodiment. In embodiments in which the GUI isimplemented using a web browser application, the server 152 (or anotherserver communicatively coupled to the server 152) may implement a webserver module (not shown in FIG. 1) that serves web pages to the webbrowser application on the computer 102, and the web pages may provideone or more GUI mechanisms such as described above.

The one or more GUI mechanisms may prompt the user to specify a databin(e.g., by indicating an ID of the databin) and to specify data to beadded to the databin (e.g., via a text-box, a file selection GUI, etc.).The computer 102 may then generate one or more API calls and send theAPI calls to the server 152. In some embodiments, the computer 102 mayestablish a connection with the server 152 as discussed above and sendthe specified data to the server 152 via the connection.

Responsive to receiving information from the computer 102 indicatingthat the user seeks to add data to a databin (e.g., via an API, aconnection, etc.), the cloud storage management module 190 locates thedatabin (e.g., with an ID, information regarding the connection, etc.)and stores the data to the databin using techniques such as discussedabove, according to an embodiment.

FIG. 7 is a flow diagram of another example method 700 for adding datato a databin, according to another embodiment. The method 700 may beimplemented in the system 100 of FIG. 1, in an embodiment, and themethod 700 is described with reference to the system 100 of FIG. 1 forexplanatory purposes. In other embodiments, however, the method 700 isimplemented in another suitable system. Similarly, in some embodiments,another suitable method for adding data to databins different than themethod 700 is implemented in the system 100.

The method 700 includes blocks from the method 600 of FIG. 6, andlike-numbered blocks are not discussed for brevity.

At block 704, user input is received via one or more GUI mechanismsassociated with adding data to a databin. The user input may include oneor more parameters such as an indication of the databin (e.g., an ID ofthe databin), an indication or indications of data to be added to thedatabin, etc.

At block 708, using the data received at block 704, one or more APIcalls are generated, the API call(s) for adding specified data to aspecified databin. In some embodiments, the computer 102 may establish aconnection with the server 152 as discussed above and send the specifieddata to the server 152 via the connection.

Similar to the method 600 of FIG. 6, one or more blocks of the method700 may be omitted, blocks may be rearranged, one or more additionalblocks may be added, etc., according to various embodiments.

Adding Data Via Web API

In some embodiments, data can be added to a databin using a suitable webAPI, such as a web API that adheres to Representational State Transfer(REST) architectural constraints, sometimes referred to as a RESTfulAPI. For instance, in some embodiments, the server 152 (or anotherserver communicatively coupled to the server 152) may implement a webserver module (not shown in FIG. 1) that is configured to handle web APIcalls.

FIG. 8A illustrates an example RESTful web API call 800 for adding datato a databin, according to an embodiment. The example of FIG. 8Acorresponds to the example of FIG. 5A. In particular, the web API call800 is for adding data “1234” to the databin corresponding to the shortID “3unzwh_n”.

The web API call 800 includes a base universal resource locator (URL)804 for adding data to databins. The web API call 800 also includes aquery portion 806. The query portion 806 includes a portion 808 utilizedfor specifying the databin to which data is to be added. In thisexample, the portion 808 includes a keyword “bin”, an operator “=”, anda short ID of the databin “3unzwh_n”. The query portion 806 alsoincludes a portion 812 utilized for specifying the data to be added tothe databin. In this example, the portion 812 includes a key “data”, anoperator “=”, and the data to be added “1234”. The portion 808 and theportion 812 are separated by a demarcation operator “&”.

FIG. 8B illustrates another example RESTful web API call 840 for addingdata to a databin, according to an embodiment. The example of FIG. 8Bcorresponds to the example of FIG. 5B. In particular, the web API call840 is for adding the data tuple “nyc” and “20.4” to the databincorresponding to the short ID “3un8f_(j)Er”.

The web API call 840 includes the base URL 804 for adding data todatabins. The web API call 840 also a query portion 842. The queryportion 842 includes a portion 844 utilized for specifying the databinto which data is to be added. In this example, the portion 844 includesa keyword “bin”, an operator “=”, and a short ID of the databin“3un8fjEr”. The query portion 842 also includes a portion 848 utilizedfor specifying the data to be added to the databin. In this example, theportion 848 includes a subportion 852 and a subportion 856. Thesubportion 852 includes a key “city”, an operator “=”, and the data tobe added “nyc”. The “=” operator indicates that the data “nyc” isassociated with the key “city”. The subportion 856 includes a key“temp”, an operator “=”, and the data to be added “20.4”. The “=”operator indicates that the data “20.4” is associated with the key“temp”. The portion 844 and the portion 848 are separated by thedemarcation operator 816. Also, the subportion 852 and the subportion856 are separated by the demarcation operator 816.

Referring now to FIG. 1, upon receiving an HTTP request corresponding toa web API call for adding data to a databin, a web server module runningon the server 152 and/or the cloud storage management module 190 parsesa query in the HTTP request (e.g., the query 806 or the query 842) todetermine the specified databin and the specified data. For example,parsing the query may include identifying one or more keywords (e.g.,“bin”), operators (e.g., “=”, “&”, etc.), and utilizing the identifiedkeyword(s) and operator(s) to parse the query. The cloud storagemanagement module 190 then uses the parsed information to locate thespecified databin and store the specified data to the specified databin.

Adding Data Via Email

Referring again to FIG. 1, in some embodiments, data can be added to adatabin using email. For instance, in some embodiments, the computer 102may implement an email application and a user can specify a databin anddata to be added to the databin using an email message. In someembodiments, the server 152 (or another server communicatively coupledto the server 152) may implement an email server module (not shown inFIG. 1), and the server 152 may receive emails corresponding to requeststo add data to databins, and, in response, store the specified data tothe specified databins.

For example, in an embodiment, a user can add data to a databin usingemail by: i) addressing an email message to an email addresscorresponding to adding data to databins, ii) including an identifier ofthe databin in a subject line of the email message, iii) including thedata to be added to the databin in a body of the email message, and iv)sending the email message.

FIG. 9A illustrates an example GUI 900 of an email application utilizedto add data to a databin, according to an illustrative embodiment. Theexample of FIG. 9A corresponds to the examples of FIGS. 5A and 8A. Inparticular, the example of FIG. 9A illustrates adding data “1234” to thedatabin corresponding to the short ID “3unzwh_n”.

In the example of FIG. 9A, the GUI 900 includes a text box 904 forentering a recipient email address. In the example of FIG. 9A, therecipient email address is an email address corresponding to adding datato databins (e.g., datadrop@wolframcloud.com). The GUI 900 also includesa text box 908 for entering a subject line for the email. In the exampleof FIG. 9A, the subject line includes the short ID of the databin towhich data is to be added. The GUI 900 also includes a text box 912 fordrafting the body of the email. In the example of FIG. 9A, the text box912 includes the data to be added, i.e., “1234”. The GUI 900 furtherincludes a button 916 that, when activated, causes the email message tobe sent.

FIG. 9B illustrates another example GUI 920 of an email applicationutilized to add data to a databin, according to an illustrativeembodiment. The example of FIG. 9B corresponds to the examples of FIGS.5B and 8B. In particular, the example of FIG. 9B illustrates adding thedata tuple “nyc” and “20.4” to the databin corresponding to the short ID“3un8fjEr”.

In the example of FIG. 9B, the GUI 920 includes a text box 924 forentering a recipient email address. In the example of FIG. 9B, therecipient email address is an email address corresponding to adding datato databins (e.g., datadrop@wolframcloud.com). The GUI 920 also includesa text box 928 for entering a subject line for the email. In the exampleof FIG. 9B, the subject line includes the short ID of the databin towhich data is to be added. The GUI 920 also includes a text box 932 fordrafting the body of the email. In the example of FIG. 9B, the text box932 includes the data to be added, i.e., “city=nyc” and “temp=20.4”).The GUI 920 further includes a button 936 that, when activated, causesthe email message to be sent.

In an embodiment, when data is to be associated with keys, an operator“=” is utilized to indicate the association. For example, theassociation between the key “city” and the value “nyc” is indicated bythe operator “=”. In other embodiments, other suitable operators may beutilized to indicate an association between keys and values. In anembodiment, different data are separated with line breaks. In otherembodiments, however, other suitable demarcation operators may beutilized such as commas, semicolons, spaces, etc.

As another example, in an embodiment, a user can add data to a databinusing email by: i) addressing an email message to an email addresscorresponding to adding data to databins, ii) including in the body ofthe email message a) an identifier of the databin, and b) the data to beadded to the databin, and iii) sending the email message. For instance,in the example of FIG. 9C, text box 928 for the subject line is leftblank. In the text box 932, however, an indication of the databin isincluded, i.e., “bin=3un8fjEr”. In an embodiment, when a databin is tobe specified in the body of the email message, the operator “bin=” isutilized to indicate that the following text correspond to an ID of adatabin. In other embodiments, other suitable operators may be utilizedto indicate text corresponds to a databin identifier.

As yet another example, in an embodiment, a user can add data to adatabin using email by: i) addressing an email message to an emailaddress corresponding to adding data to databins and also specifying aparticular databin, ii) including in the body of the email message thedata to be added to the databin, and iii) sending the email message. Forinstance, in the example of FIG. 9D, the recipient email addressincludes the databin ID “3un8fjEr”. In an embodiment, when a databin isto be specified in the recipient email address, the operator “+” isincluded after the base email address and is utilized to indicate thatthe following text (prior to the “@” operator) correspond to an ID of adatabin. In other embodiments, other suitable operators may be utilizedto indicate text in the email address corresponds to a databinidentifier.

Referring now to FIG. 1, upon receiving an email message correspondingto a web API call for adding data to a databin, an email server modulerunning on the server 152 and/or the cloud storage management module 190parses the email message to determine the specified databin and thespecified data. For example, parsing the query may include identifyingone or more keywords (e.g., “bin”), operators (e.g., “=”, “+”, space,etc.), and utilizing the identified keyword(s) and operator(s) to parsethe email message. The cloud storage management module 190 then uses theparsed information to locate the specified databin and store thespecified data to the specified databin.

Adding Data Via Twitter®

Referring again to FIG. 1, in some embodiments, data can be added to adatabin using suitable messaging applications other than email, such asa social media application or another suitable messaging application.For instance, in some embodiments, the computer 102 may implement aTwitter® application and a user can specify a databin and data to beadded to the databin using a Twitter® message. In some embodiments, theserver 152 (or another server communicatively coupled to the server 152)may implement a Twitter® application module (not shown in FIG. 1), andthe server 152 may receive twitter messages corresponding to requests toadd data to databins, and, in response, store the specified data to thespecified databins.

For example, in an embodiment, a user can add data to a databin using aTwitter® message by: i) addressing a Twitter® message to a usernamecorresponding to adding data to databins, ii) including an identifier ofthe databin in the Twitter® message, iii) including the data to be addedto the databin in the Twitter® message, and iv) sending the Twitter®message.

FIG. 10A illustrates an example GUI 1000 of a Twitter® applicationutilized to add data to a databin, according to an illustrativeembodiment. The example of FIG. 10A corresponds to the examples of FIGS.5A, 8A, and 9A. In particular, the example of FIG. 10A illustratesadding data “1234” to the databin corresponding to the short ID“3unzwh_n”.

In the example of FIG. 10A, the GUI 1000 includes a text box 1004 forentering a recipient user ID and text to be included in the message. TheGUI 1000 also includes a button 1008 that, when activated, causes themessage to be sent.

In the example of FIG. 10A, a recipient user ID 1012 has been added tothe text box 1004. The recipient user ID 1012 is a user ID correspondingto adding data to databins (e.g., @WolframDataDrop). The text box 1004also includes the short ID 1016 of the databin to which data is to beadded (i.e., “3unzwh_n”). The text box 1004 also includes the data 1020to be added, i.e., “1234”. In an embodiment, the databin ID 1016 and thedata 1020 are demarcated by a semicolon 1024. In other embodiments,another suitable operator may be utilized for demarcating the databin ID1016 and the data 1020.

FIG. 10B illustrates another example GUI 1040 of a Twitter® applicationutilized to add data to a databin, according to an illustrativeembodiment. The example of FIG. 10B corresponds to the examples of FIGS.5B, 8B, and 9B. In particular, the example of FIG. 10B illustratesadding data tuples “city”->“nyc” and “temp”->20.4 to the databincorresponding to the short ID “3un8fjEr”.

In the example of FIG. 10B, the GUI 1040 includes the text box 1004 andthe button 1008 as in the example of FIG. 10A. The recipient user ID1012 has been added to the text box 1004. The text box 1004 alsoincludes the short ID 1044 of the databin to which data is to be added(i.e., “3un8fjEr”). The text box 1004 also includes the data 1048, 1052to be added, i.e., city=nyc and temp=20.4. In an embodiment, the databinID 1044, the data 1048, and the data 1052 are demarcated by semicolons1024. In other embodiments, another suitable operator may be utilizedfor demarcating the databin ID 1044 from the data 1048, 1052, and/ordemarcating the data 1048 from the data 1052.

In an embodiment, when data is to be associated with keys, an operator“=” is utilized to indicate the association. For example, theassociation between the key “city” and the value “nyc” is indicated bythe operator “=”. In other embodiments, other suitable operators may beutilized to indicate an association between keys and values. In anembodiment, different data are separated with line breaks. In otherembodiments, however, other suitable demarcation operators may beutilized such as commas, semicolons, spaces, etc.

Referring now to FIG. 1, a Twitter® application module (not shown)running on the server 152 obtains a Twitter® message using a Twitter®API, in an illustrative embodiment. For example, in an embodiment, theTwitter® application module uses the Twitter® API to obtain, from aTwitter® server, Twitter® messages addressed to a particular user ID(e.g., @WolframDataDrop). The Twitter® application module and/or thecloud storage management module 190 parses the Twitter® message todetermine the specified databin and the specified data. For example,parsing the query may include identifying one or more keywords (e.g.,“bin”), operators (e.g., “=”, “;”, space, etc.), and utilizing theidentified keyword(s) and operator(s) to parse the Twitter® message. Thecloud storage management module 190 then uses the parsed information tolocate the specified databin and store the specified data to thespecified databin.

Adding Data with a Sensor Device

Referring again to FIG. 1, in some embodiments, the sensor device 198can add data to a databin using a suitable API, such as the web APIdiscussed above with reference to FIGS. 8A and 8B.

FIG. 11 is a block diagram of an example sensor device 1100, accordingto an embodiment. The sensor device 1100 may be utilized as the sensordevice 198 of FIG. 1, according to some embodiments. The sensor device1100 may be configured to add data to a databin using a suitable API,such as the web API discussed above with reference to FIGS. 8A and 8B.

The sensor device 1100 includes one or more processors 1104 (sometimereferred to herein as “the processor 1104” for brevity) and one or morememory devices 1108 (sometime referred to herein as “the memory 108” forbrevity).

The sensor device 1100 also includes, or is coupled to, one or moresensors 1112 for measuring real world physical parameters such astemperature, pressure, sound, motion, light, speed, acceleration,geographic position, physical orientation, etc. Thus, in variousembodiments, the one or more sensors 1112 include one of, or anysuitable combination of two or more of, a temperature sensor, a pressuresensor, a microphone, a motion sensor, a light sensor, a camera sensor,an accelerometer, a magnetometer, a gyroscopic sensor, a current sensor,a voltage sensor, an electrical power sensor, a position sensor, achemical sensor, etc.

The sensor device 1100 may include, or be coupled to, one or more inputdevices 1114. For example, in some embodiments, the sensor device 1100may include one of, or any suitable combination of two or more of, akeypad, one or more buttons, one or more knobs, one or more sliders, atouch screen that overlays a display device, etc. In other embodiments,however, the sensor device 1100 omits the one or more input devices1114. In some embodiments, the sensor device 1100 may include, or becoupled to, one or more display devices 1116. In other embodiments,however, the sensor device 1100 omits the one or more display devices1116.

In some embodiments, the sensor device 1100 includes one or more networkinterface devices 1120, such as one of, or any suitable combination oftwo or more of, a WiFi network interface, a mobile telephony networkinterface, a personal area network (PAN) network interface (e.g., aBluetooth® network interface), an Ethernet network interface, apositioning system radio (e.g., a GPS radio), etc. The processor 1104,the memory device 1108, the one or more sensor devices 1112 (sometimereferred to herein as “the sensor device 112” for brevity), the one ormore input devices 1114 (sometime referred to herein as “the inputdevice 1114” for brevity), the one or more display devices 1116(sometime referred to herein as “the display device 1116” for brevity),the one or more network interface devices 1120 (sometime referred toherein as “the network interface device 1120” for brevity), etc., may becommunicatively coupled via one or more busses 1124 (sometime referredto herein as “the bus 1124” for brevity). In other embodiments, thesensor device 1100 may have other suitable structures and/or components.

The processor 1104 may comprise one or more general purpose processors(e.g., a central processing unit), one or more special purposeprocessors (e.g., a co-processor, an embedded processor, etc.). At leastone of the processor(s) 1104 executes machine readable instructionsstored in the memory 1108. The memory device(s) 1108 include one or moreof RAM, ROM, a FLASH memory, etc.

In some embodiments, the memory 1108 may store a cloud storage front endmodule 1144 that enables adding data to databins, according to variousembodiments. In some embodiments, the cloud storage front end 1144 maybe the same as the cloud storage front end 144 discussed above, or areduced-size, reduced-functionality version of the cloud storage frontend 144. For example, in an embodiment, the cloud storage front endmodule 1144 may enable adding data to already existing databins, but isnot configured for creating databins.

In some embodiments, the memory 1108 may store a computationalapplication 1140. In some embodiments, the computational application1140 may be same as the computational application 140 of FIG. 1, or areduced-size, reduced-functionality version of the computationalapplication 140. In some embodiments, the cloud storage front end module1144 is included in the computational application 1140. In someembodiments, however, the computational application 1140 is omitted andthe cloud storage front end 1144 is a standalone application and/ormodule. In some embodiments, the cloud storage front end 1144 isincorporated into another suitable application different than thecomputational application 1140.

In various embodiments, the sensor device 1100 may be a standalonedevice, or may be included in another device or system such as a stillphoto camera, a video camera, a security system, an airconditioning/heating control system, etc.

In some embodiments, the cloud storage front end 1144 can, when executedby the processor 1104, add data to a databin using a suitable API, suchas the web API discussed above with reference to FIGS. 8A and 8B. Forexample, the cloud storage front end 1144 may, when executed by theprocessor 1104, cause the sensor device 1100 to send API calls foradding data to a databin to be sent to the server 152 via the network150 using the network interface device 1120. In some embodiments, thecloud storage front end 1144 may establish a connection with the server152 as discussed above and send the specified data to the server 152 viathe connection.

In some embodiments, the cloud storage front end 1144 may be included inthe memory 1108 and already configured, upon sale of the sensor device1100, for storing data to a databin. For example, a manufacturer of, adistributor of, etc., the sensor device 1100 may create databins, orhave a databins created, for sensor devices 1100 to be sold,distributed, etc. Additionally, the cloud storage front end 1144 may bealready configured, upon the sensor device 1100 being turned on by auser, with a databin ID, key/value association(s), etc., correspondingto a created databin so that the cloud storage front end 1144 can causethe sensor device 1100 to transmit API calls, establish a connection,send data to the server 152 via such a connection, etc., to add data tothe already created databin after establishing a network connection tothe network 150. For example, the cloud storage front end 1144 may beconfigured to cause such API calls to be transmitted, to send data to asocket, etc., periodically and/or in response to specific events, suchas events detected by the sensor device 1100. In some embodiments, thesensor device 1100 may thus begin storing data to an already createddatabin shortly after the sensor device 1100 is turned on by a user andthe sensor device 1100 has established a connection to the network 150.

Similarly, in some embodiments, the cloud storage front end 1144 may beincluded in the memory 1108 and already configured, upon sale of thesensor device 1100, for creating a databin and then storing data to thecreated databin. Additionally, the cloud storage front end 1144 may bealready configured, upon the sensor device 1100 being turned on by auser, to cause the sensor device 1100 to transmit API calls for creatinga databin and then adding data to the created databins afterestablishing a connection to the network 150. For example, the cloudstorage front end 1144 may be configured to cause API calls for storingdata to a databin to be transmitted periodically and/or in response tospecific events, such as events detected by the sensor device 1100. Asanother example, the cloud storage front end 1144 may be configured toestablish a connection with the server 152 and send data to a socketassociated with the connection periodically and/or in response tospecific events, such as events detected by the sensor device 1100. Insome embodiments, the sensor device 1100 may thus create a databin andbegin storing data to the databin shortly after the sensor device 1100is turned on by a user and the sensor device 1100 has established aconnection to the network 150.

In some embodiments, the cloud storage front end 1144 may be included inthe memory 1108 and already configured, upon sale of the sensor device1100, for receiving a databin ID from a user and then storing data to adatabin corresponding to the received databin ID. For example, a usermay create a databin using the computer 102, for example. Additionally,the cloud storage front end 1144 may be already configured, upon thesensor device 1100 being turned on by a user, to prompt the user toprovide the databin ID and optionally key/value association(s), etc.,corresponding to the created databin so that the cloud storage front end1144 can cause the sensor device 1100 to transmit API calls for addingdata to the databin, to send data via a connection to the server 152,etc. For example, the cloud storage front end 1144 may be configured tocause such API calls to be transmitted, to send data to a socket, etc.,periodically and/or in response to specific events, such as eventsdetected by the sensor device 1100.

In some embodiments, the cloud storage front end 1144 is not present inthe memory 1108 when the sensor device 1100 is purchased by the user.Rather, the cloud storage front end 1144 is added to the memory 1108 bythe user. For example, the user may download the cloud storage front end1144 from the server 152 or another server and cause the cloud storagefront end 1144 to be stored in the memory 1108. As another example, theuser may create the cloud storage front end 1144 and then store thecloud storage front end 1144 in the memory 1108. After the cloud storagefront end 1144 is stored in the memory 1108, the cloud storage front end1144 may operate in a manner such as discussed above, according to someembodiments.

Thus, in some embodiments, a sensor device 1100 is configured toautomatically begin storing data in a databin (e.g., periodically, inresponse to specific events, etc.) responsive to being turned on by auser, for example. A user can then later access the databin. Forexample, in an embodiment, the cloud storage front end 1144 may beconfigured to prompt the user with instructions for accessing thedatabin. Instructions for accessing the databin may include a websiteaddress corresponding to the server 152, in an embodiment. Instructionsfor accessing the databin may include a databin ID corresponding to thedatabin, in an embodiment.

For instance, in embodiments in which the sensor device 1100 includes adisplay 1116, the cloud storage front end 1144 may be configured tocause the instructions for accessing the databin to be displayed on thedisplay 1116. In some embodiments, a web page server module (not shown)is stored in the memory 1108, and the sensor device 1100 may beconfigured to allow a user to interact with the sensor device 1100 viaweb pages served by the web page server module. For example, the servermodule may serve web pages that allow a user to change configurationsettings of the sensor device 1100, obtain data from the sensor device1100, etc. For example, a user can utilize a computer (e.g., thecomputer 102 or a similar computer) to communicate with the sensordevice 1100 via WiFi, Ethernet, etc., according to an illustrativeembodiment. In such embodiments, the server module may serve web pagesthat present instructions for accessing the databin.

In some embodiments, instructions for accessing the databin may beprinted on packaging in which the sensor device 1100 was shipped and/orsold. In some embodiments, instructions for accessing the databin may beprinted on an insert included in the packaging in which the sensordevice 1100 was shipped and/or sold. In some embodiments, instructionsfor accessing the databin may be provided in web page(s) of a websiteowned, operated, or otherwise associated with a manufacturer ordistributer of the sensor device 1100.

In some embodiments, a web server module implemented by the server 152(or another server) may permit a user to access (e.g., obtain data from,manage settings, etc.) a databin to which a sensor device 1100 isautomatically storing data. For example, the web server module may servea web page(s) with one or more GUI mechanisms that allow a user tospecify the sensor device 1100, e.g., with one or more of a unique ID ofthe sensor device 1100 such as a UUID, a serial number, a manufacturename, a manufacturer ID, etc. As an illustrative example, the web servermodule and/or the server 152 may maintain a database of sensor deviceIDs and associated databin IDs. Thus, when a user provides informationspecifying the sensor device 1100 using the one or more GUI mechanisms,the web server module and/or the server 152 can determine the databin towhich the sensor device 1100 is storing data by analyzing the databaseof sensor device IDs and associated databin IDs. In some embodiments,the web server module may also serve a web page(s) with one or more GUImechanisms that allow a user to associate the determined databin withthe user instead of, or in addition to, the sensor device 1100.

Referring again to FIG. 1, in some embodiments, the cloud storagemanagement module 190 may be implemented as a multi-threaded servermodule to handle high volume and/or high rate accesses to cloud storageobjects 184. For example, different threads may handle differentrequests to add data to databins, in an embodiment. As a more specificexample, different threads may handle different requests to add data toa same databin, in an embodiment.

Accessing Data in Cloud Storage Objects

Referring again to FIG. 1, in some embodiments, the system 100 providesa plurality of mechanisms for accessing data in (e.g., retrieving datafrom) databins using techniques such as described above (or using othersuitable techniques). In such embodiments, the plurality of availablemechanisms for accessing data in databins may provide much flexibilityfor users to access data for analysis by the computational application140 (and/or a separate data analysis application). For example, in anillustrative embodiment, data in a databin can be accessed i)programmatically via the computational application 140, ii) via one ormore web pages served by a web server module implemented by the server152 (or another server coupled to the server 152), etc.

In other embodiments, the system only provides one of, or a subset of,the mechanisms for accessing data in databins discussed above, and/orprovides one or more other suitable mechanisms.

Accessing Data Programmatically

In some embodiments, the computational application 140 provides abuilt-in function and/or built-in mechanisms for accessing data indatabins. For example, the computational application 140 may provide abuilt-in function with a descriptive keyword such as “Databin”, wherethe built-in function is for accessing data in cloud storage objects 184(e.g., databins). Thus, in some embodiments, a user can utilize thecomputational application 140 and the Databin function to access data incloud storage objects 184 (“databins”). For example, in an embodiment,in response to a user entering the built-in function Databin into aworkspace such as a notebook and causing the computational application140 to evaluate the built-in function (e.g., by pressing “Enter” ortaking some other suitable action), the computational application 140interacts with the cloud storage management module 190, causing thecloud storage management module 190 to retrieve data from a specifieddatabin. For example, the computational application 140 may evaluate theDatabin function entered within the workspace, where a parameter of theDatabin function specifies a particular databin. Responsive to theevaluation, computational application 140 may use an API to cause thecloud storage management module 190 to retrieve data from the specifieddatabin. The cloud storage management module 190 may then send theretrieved data to the computational application 140, e.g., using an API.

Responsive to receiving information from the cloud storage front end 144indicating that the user seeks to access a specified databin (e.g., viaone or more API calls), the cloud storage management module 190 locatesthe specified data bin in the cloud storage 180 and retrieves data inthe databin.

As discussed above, in some embodiments, the Databin function includesan argument that a user can utilize to specify a databin. In anillustrative embodiment, the Databin function has a format as follows:

Databin[bin], where bin is an argument specifying a unique ID associatedwith a databin. In various embodiments, the argument bin can be of oneformat or multiple formats, such as one or more of a short ID, acomplete UUID, a short URL, a long URL, etc. In some embodiments, theDatabin function optionally includes one or more other arguments that auser can utilize to specify which data in the databin are to beaccessed. In an illustrative embodiment, the Databin function has aformat as follows:

Databin[bin, params], where bin is the argument specifying a unique IDassociated with a databin, and params are one or more other parametersspecifying which data in the databin are to be accessed. In someembodiments, the one or more other parameters may specify a range ofentries in terms of an entry index or index range. In some embodiments,the one or more other parameters may specify a range of entries in termsof time. In some embodiments, the one or more other parameters mayspecify a range of entries in terms of keys. Several example parametersthat may be utilized are set forth below. In various embodiments, one,several, all, or none of the following parameters may be utilized:

Databin[bin, n]

where n indicates the first n entries in a databin.

Databin[bin, −n]

where −n indicates the most recent n entries in a databin.

Databin[bin, {m, n}]

where m and n indicates entries m through n in a databin, with negativenumbers counting from the end (i.e., most recent entries).

Databin[bin, {m, n, s}]

where {m, n, s} indicates entries m through n with step s.

Databin[bin, time]

where time indicates entries going back for the quantity of timespecified by time.

Databin[bin, date]

where date indicates entries from the specified date to now.

Databin[bin, {data, date2}]

where {data, date2} indicates entries in a databin between the specifieddates, inclusive.

Databin[bin, range, {“key1”, “key2”, . . . }]

where range indicates a specified range of entries (using parameterssuch as described above), and {“key1”, “key2”, . . . } indicates onlyelements in the databin associated with keys “key1”, “key2”, . . . .

The cloud storage management module 190 is configured to utilize the IDin the one or more API calls to locate the specified data bin in thecloud storage 180. Additionally, in some embodiments, the cloud storagemanagement module 190 is configured to utilize other parameters, ifpresent, in the one or more API calls to determine which data in thespecified databin are to be retrieved. The cloud storage managementmodule 190 then retrieves the specified data from the specified databin.

In an embodiment, after the cloud storage management module 190retrieves data from the databin, the cloud storage management module 190returns the data to the cloud storage front end 144 (e.g., via one ormore API calls, via a connection, etc.). Thus, in an embodiment,responsive to evaluation of the Databin function in a workspace (e.g., anotebook), the computational application 140 displays and/or makesavailable the returned data in the workspace. In an embodiment in whichthe computational application 140 is configured to internally representdifferent types of data as symbolic expressions, databins themselves arerepresented as symbolic expressions. Thus, in some embodiments and/orscenarios, responsive to evaluation of the Databin function in aworkspace (e.g., a notebook), the computational application 140 returnsa symbolic databin object to the same workspace. In some embodiments,responsive to evaluation of the Databin function in a workspace (e.g., anotebook), the computational application 140 returns, to the sameworkspace, data in a format recognized by the computational application140 so that the data can be operated upon, or processed, by thecomputational application 140 immediately without first having to importthe data into the workspace by some other user-directed action (e.g., acut and paste operation) and/or without having to first convert the datato the format recognized by the computational application 140 by someother user-directed action (e.g., a convert-to operation, a save-asoperation, etc.).

FIG. 12 is an example notebook in which a programmer utilizes theDatabin function to access a databin in the cloud storage 180 (FIG. 1),according to an embodiment. The programmer has entered into the notebookan expression bin=Databin[“1qGFQ8v”]. The expression includes an ID 1204of a databin, e.g., 1qGFQ8v. The computational application 140 evaluatesthe entered expression and, in response, utilizes an API to cause thecloud storage management module 190 to access the specified databin. Forexample, the cloud storage front end 144 sends one or more API calls tothe cloud storage management module 190 via the network 150. Next, thecloud storage management module 190 locates the databin using the ID1204, and retrieves data from the databin. Next, the cloud storagemanagement module 190 returns the retrieved data to the cloud storagemanagement module 190 via the network 150.

The computational application 140 makes the retrieved data available forprocessing in the notebook. In an embodiment, the retrieved data is in aformat that is recognized by the computational application 140 so thatthe retrieved data can be immediately processed by the computationalapplication 140 without other user-directed action being required, suchas a user-directed action to import the data into the workspace, auser-directed action to convert the data to a new format, etc. In theexample of FIG. 12, the computational application 140 sets the variable“bin” equal to a symbolic databin object corresponding to the retrieveddata from the databin. The computational application 140 adds a graphic1208 to the notebook to visually represent the symbolic databin objectin the notebook.

In the example of FIG. 12, the programmer utilizes a DateListPlotfunction to analyze the retrieved databin. DateListPlot is a built-infunction of computational application 140 that has the following format:

DateListPlot[{date1, v1}, {date2, v2}, . . . ]

where values v are associated with dates date. The DateListPlot functionplots the values v with respect to the associated dates. In the exampleof FIG. 12, the databin includes first values associated with a key “HR”and second values associated with a key “SpO2”. Additionally, asdiscussed above, each entry in a databin is associated with a timestamp,at least in some embodiments. Thus, in some embodiments, theDateListPlot function may utilize the timestamps of entries to generateplots of each of the first values associated with a key “HR” and secondvalues associated with a key “SpO2”, as shown in FIG. 12. Moreover, insome embodiments, the DateListPlot function may utilize the keyassociations of entries to determine that separate plots i) for thefirst values associated with a key “HR” and ii) for the second valuesassociated with a key “SpO2”, should be generated. Thus, thecomputational application 140 utilizes knowledge of the format of thedatabin to intelligently process data in the databin.

FIG. 13 is an example notebook in which a programmer utilizes theDatabin function to access a databin in the cloud storage 180 (FIG. 1),according to an embodiment. The programmer has entered into the notebookan expression bin=Databin[“3pw3N73Q”]. The expression includes an ID1304 of a databin, e.g., 3pw3N73Q. The computational application 140evaluates the entered expression and, in response, utilizes an API tocause the cloud storage management module 190 to access the specifieddatabin. For example, the cloud storage front end 144 sends one or moreAPI calls to the cloud storage management module 190 via the network150. Next, the cloud storage management module 190 locates the databinusing the ID 1304, and retrieves data from the databin. Next, the cloudstorage management module 190 returns the retrieved data to the cloudstorage management module 190 via the network 150.

The computational application 140 makes the retrieved data available forprocessing in the notebook. In an embodiment, the retrieved data is in aformat that is recognized by the computational application 140 so thatthe retrieved data can be immediately processed by the computationalapplication 140 without other user-directed action being required, suchas a user-directed action to import the data into the workspace, auser-directed action to convert the data to a new format, etc. In theexample of FIG. 13, the computational application 140 sets the variable“bin” equal to a symbolic databin object corresponding to the retrieveddata from the databin. The computational application 140 adds a graphic1308 to the notebook to visually represent the symbolic databin objectin the notebook.

In the example of FIG. 13, the programmer then utilizes a Histogramfunction to analyze the retrieved databin. Histogram is a built-infunction of the computational application 140 that has the followingformat:

Histogram [{v1, v2, . . . }]

where a histogram of values v is generated. Additionally, the Histogramfunction may have the following alternative format:

Histogram [{data1, data2, . . . }]

where multiple histograms of data sets data are generated.

In the example of FIG. 13, the databin includes first values associatedwith a key “Humidity”, second values associated with a key “Light”,third values associated with a key “Pressure”, and fourth valuesassociated with a key “Temperature”. Thus, in some embodiments, in someembodiments, the Histogram function may utilize the key associations ofentries to determine that separate histograms i) for the first valuesassociated with a key “Humidity”, ii) for the second values associatedwith a key “Light”, iii) for the third values associated with a key“Pressure”, and iv) for the fourth values associated with the key“Temperature”, should be generated. Thus, the computational application140 utilizes knowledge of the format of the databin to intelligentlyprocess data in the databin.

In the example of FIG. 13, the programmer then utilizes a MinMaxfunction to analyze data in the retrieved databin. MinMax is a built-infunction of the computational application 140 that has the followingformat:

MinMax [list]

where the function determines the minimum value in the list and themaximum value in the list, and then returns a list having the minimumvalue and the maximum value.

The programmer further utilizes a Values function, within the MinMaxfunction. Values is a built-in function of the computational application140 that has the following format:

Values[list][key]

where the function extracts values from a list that are associated withthe key, and then returns a list having the extracted values.

In the example of FIG. 13, the programmer used the key 1320(temperature) with the Values function, and thus the Values functionextracts all of the values in the databin that are associated with thekey Temperature. Additionally, the MinMax function determines, fromamong the values in the databin that are associated with the keyTemperature, the minimum value and the maximum value. Thus, thecomputational application 140 returns a list having the minimumTemperature value and the maximum Temperature value in the databin.Accordingly, the computational application 140 utilizes knowledge of theformat of the databin to intelligently process data in the databin.

FIG. 14 is a flow diagram of an example method 1400 for retrieving datafrom a databin, according to an embodiment. The method 1400 may beimplemented in the system 100 of FIG. 1, in an embodiment, and themethod 1400 is described with reference to the system 100 of FIG. 1 forexplanatory purposes. In other embodiments, however, the method 1400 isimplemented in another suitable system. Similarly, in some embodiments,another suitable method for retrieving data from databins different thanthe method 1400 is implemented in the system 100.

At block 1404, programmer input corresponding to a built-in function ofthe computational application 140 is received, where the built-infunction is for retrieving data from databins. In an embodiment, theprogrammer input may include i) a keyword (e.g., Databin) correspondingto the built-in function, and ii) one or more parameters of the built-infunction such as described above. For example, a first parameter mayindicate the databin. In some embodiments and/or scenarios, a secondparameter (or parameters) may indicate which data in the databin is tobe retrieved. The programmer input may be received via one or more userinput devices of the computer 102, and input into a document such as anotebook, a spreadsheet, etc.

At block 1408, the programmer input is evaluated by the computationalapplication 140, and, responsive to the evaluation, one or more APIcalls may be generated by the cloud storage front end module 144, wherethe one or more API calls correspond to requests for data to beretrieved from the specified databin, and the one or more API callsoptionally may include indication(s) of one or more parameters such asdescribed above.

The one or more API calls may be transmitted from the computer 102 tothe server 152 via the network 150. At block 1412, the API call(s) arereceived by the server 152.

At block 1416, the one or more API calls are evaluated by the cloudstorage management module 190, and, responsive to the evaluation, datais retrieved from the databin at block 1420.

At block 1424, the cloud storage management module 190 may return theretrieved data to the cloud storage front end module 144 according to anAPI. For example, the retrieved data may be transmitted by the server152 to the computer 102 via the network 150, in an embodiment.

At block 1428, the computational application may make the retrieved dataavailable in the document. In an embodiment, the retrieved data is in aformat that is recognized by the computational application 140 so thatthe retrieved data can be immediately processed by the computationalapplication 140 without other user-directed action being required, suchas a user-directed action to import the data into the workspace, auser-directed action to convert the data to a new format, etc.

In various other embodiments, one or more blocks of the method 1400 maybe omitted, blocks may be rearranged, one or more additional blocks maybe added, etc.

Accessing Data Via Web Page, App, Etc.

In some embodiments, data in a databin can be accessed using a GUIimplemented by the computer 102 (FIG. 1), where the GUI utilizes one ormore suitable GUI mechanisms, such as one or more of i) one or morebuttons, ii) one or more hypertext links, iii) one or more pull-downmenus, iv) one or more pop-up menus, v) one or more text boxes, etc.Referring again to FIG. 1, in an embodiment, in response to a selectingto retrieve data from a databin with the GUI, the computer 102 interactswith the cloud storage management module 190, causing the cloud storagemanagement module 190 to retrieve data from the databin. For instance,the GUI may be implemented using a web browser application executed bythe computer 102, in an embodiment. As another example, the GUI may beimplemented using a mobile app executed by the computer 102, in anembodiment. In embodiments in which the GUI is implemented using a webbrowser application, the server 152 (or another server communicativelycoupled to the server 152) may implement a web server module (not shownin FIG. 1) that serves web pages to the web browser application on thecomputer 102, and the web pages may provide one or more GUI mechanismssuch as described above.

The one or more GUI mechanisms may prompt the user to specify a databin(e.g., by indicating an ID of the databin, selecting a databin from alist, selecting a button requesting to download data from a selecteddatabin, etc.). Optionally, the one or more GUI mechanisms may promptthe user to specify which data is to be retrieved from the databin(e.g., via a text-box, buttons, menu selections, etc.). The computer 102may then generate one or more API calls and send the API calls to theserver 152.

Responsive to receiving information from the computer 102 indicatingthat the user seeks to retrieve data from a databin (e.g., via an API,via one or more HTTP requests, etc.), the cloud storage managementmodule 190 locates the databin (e.g., with an ID) and retrieves datafrom the databin using techniques such as discussed above, according toan embodiment.

Then, the cloud storage management module 190 may return the retrieveddata to the computer 102. For example, in an embodiment, the retrieveddata may be transmitted by the server 152 to the computer 102 via thenetwork 150. In an embodiment in which the server 152 implements or iscoupled to a web server, the web server may generate one or more webpages that include the retrieved data, and may then provide the one ormore web pages to the computer 102, as an example. In anotherembodiment, the server 152 may provide the retrieved data to thecomputer 102 via an API of a mobile app, as another example. In yetanother embodiment, the server 152 may provide the retrieved data to thecomputer 102 via a connection, as another example.

In some embodiments, a web page associated with a databin may provide auser interface mechanism (e.g., a GUI such as a link, a button, etc.)for causing the answering system 194 (FIG. 1) to analyze the databinand/or data within the databin. Referring again to FIG. 1, in anembodiment, in response to selecting such a GUI mechanism, the computer102 interacts with the cloud storage management module 190, causing thecloud storage management module 190 to send data from the databin to theanswering system 194 and/or to prompt the answering system 194 toretrieve data from the databin. For instance, the GUI may be implementedusing a web browser application executed by the computer 102, in anembodiment. As another example, the GUI may be implemented using amobile app executed by the computer 102, in an embodiment. Inembodiments in which the GUI is implemented using a web browserapplication, the server 152 (or another server communicatively coupledto the server 152) may implement a web server module (not shown inFIG. 1) that serves web pages to the web browser application on thecomputer 102, and the web pages may provide one or more GUI mechanismssuch as described above.

The answering system 194 may be configured to recognize the format ofthe databin, and may utilize knowledge of the format to analyze thedatabin and/or contents of the databin. In an embodiment, the answeringsystem 194 may be configured to perform default analyses and/oroperations on the databin and/or contents of the databin, such asdisplaying metadata regarding the databin, displaying content of thedatabin, plotting contents of the databin, determining and displayingstatistical information regarding content of the databin, such as one ormore of a median value of contents (such as values associated with akey), an average value of contents (such as values associated with akey), a variance of contents (such as values associated with a key), aminimum value of contents (such as values associated with a key), astandard deviation of contents (such as values associated with a key), amaximum value of contents (such as values associated with a key), aminimum value of contents (such as values associated with a key), etc.In some embodiments, the answering system 194 may include or be coupledto a web server that is configured to generate a web page(s) thatdisplays results of the analyses and/or operations discussed above, andthe web server may send the web page(s) to the user computer 102 via thenetwork 150. In some embodiments, the answering system 194 may beconfigured to send results of the analyses and/or operations discussedabove to the server 152, and a web server implemented by or coupled tothe server 152 may generate a web page(s) that displays results of theanalyses and/or operations discussed above and send the web page(s) tothe user computer 102 via the network 150.

FIGS. 15A and 15B are an illustration of an example web page 1500 thatdisplays results of analyses and/or operations performed on an exampledatabin by an answering system 154, according to an illustrativeembodiment.

In some embodiments, the answering system 194 may be configured toperform analyses on the data using techniques such as described in U.S.patent application Ser. No. 13/763,568, filed Feb. 8, 2013 and/or U.S.patent application Ser. No. 14/216,461, filed Mar. 17, 2014.

Accessing Data Via Answering System 194

In some embodiments, data in a databin can be accessed using theanswering system 194 (FIG. 1), where the answering system 194 providesone or more suitable GUI mechanisms, such as one or more of i) one ormore buttons, ii) one or more hypertext links, iii) one or morepull-down menus, iv) one or more pop-up menus, v) one or more textboxes, etc., to enable a user to specify a databin or databins.Referring again to FIG. 1, in an embodiment, in response to a selectingto analyze data from a databin with the GUI, the computer 102 interactswith the answering system 194, causing the answering system 194 toretrieve data from the databin and to perform analyses and/or operationson the databin and/or content in the databin. For instance, the GUI maybe implemented using a web browser application executed by the computer102, in an embodiment. As another example, the GUI may be implementedusing a mobile app executed by the computer 102, in an embodiment. Inembodiments in which the GUI is implemented using a web browserapplication, the answering system 194 (or a server communicativelycoupled to the answering system 194) may implement a web server module(not shown in FIG. 1) that serves web pages to the web browserapplication on the computer 102, and the web pages may provide one ormore GUI mechanisms such as described above.

The answering system 194 may be configured to recognize the format ofthe databin, and may utilize knowledge of the format to analyze thedatabin and/or contents of the databin. In an embodiment, the answeringsystem 194 may be configured to perform default analyses and/oroperations on the databin and/or contents of the databin, such asdisplaying metadata regarding the databin, displaying content of thedatabin, plotting contents of the databin, determining and displayingstatistical information regarding content of the databin, such as one ormore of a median value of contents (such as values associated with akey), an average value of contents (such as values associated with akey), a variance of contents (such as values associated with a key), aminimum value of contents (such as values associated with a key), astandard deviation of contents (such as values associated with a key), amaximum value of contents (such as values associated with a key), aminimum value of contents (such as values associated with a key), etc.In some embodiments, the answering system 194 may include or be coupledto a web server that is configured to generate a web page(s) thatdisplays results of the analyses and/or operations discussed above, andthe web server may send the web page(s) to the user computer 102 via thenetwork 150.

FIGS. 16A and 16B are an illustration of an example web page 1600 thatdisplays results of analyses and/or operations performed on an exampledatabin by an answering system 154, according to an illustrativeembodiment. The web page 1600 includes a text box 1604 for enteringnatural language input to be analyzed by the answering system 194, and auser prompts the answering system 194 to analyze the input in the box1604 by pressing Enter, selecting a button (not shown), etc. In theexample of FIGS. 16A and 16B, the user has entered the text “databin1EyATYFR”, and the answering system 194 interprets this input as arequest to analyze data in the databin having the ID 1EyATYFR. Inresponse, answering system 154 accesses the specified databin andperforms analyses/operations such as described above. Results ofanalyses and/or operations performed by the answering system 154 arethen displayed in the web page 1600.

Referring again to FIG. 1, in some embodiments, the cloud storagemanagement module 190 may be implemented as a multi-threaded servermodule to handle high volume and/or high rate accesses to cloud storageobjects 184. For example, different threads may handle differentrequests to access data in databins, in an embodiment. As a morespecific example, different threads may handle different requests toaccess data in a same databin, in an embodiment.

As another example, different threads additionally or alternatively mayhandle different types of requests regarding the same databin, e.g.,different threads may handle requests to add data to a databin and toaccess data in the same databin.

Deleting Data in Cloud Storage Objects

Referring again to FIG. 1, in some embodiments, the system 100 providesone or more mechanisms for deleting data in databins using techniquessimilar to techniques described above (or using other suitabletechniques). For example, in an illustrative embodiment, data in adatabin can be deleted i) programmatically via the computationalapplication 140, ii) via one or more web pages served by a web servermodule implemented by the server 152 (or another server coupled to theserver 152), etc.

In some embodiments, the computational application 140 provides abuilt-in function and/or built-in mechanisms for deleting data indatabins. For example, the computational application 140 may provide abuilt-in function with a descriptive keyword such as“DeleteDatabinData”, where the built-in function is for deleting data incloud storage objects 184 (e.g., databins). Thus, in some embodiments, auser can utilize the computational application 140 and theDeleteDatabinData function to delete data in cloud storage objects 184(“databins”). For example, in an embodiment, in response to a userentering the built-in function DeleteDatabinData into a workspace suchas a notebook and causing the computational application 140 to evaluatethe built-in function (e.g., by pressing “Enter” or taking some othersuitable action), the computational application 140 interacts with thecloud storage management module 190, causing the cloud storagemanagement module 190 to delete data from a specified databin. Forexample, the computational application 140 may evaluate theDeleteDatabinData function entered within the workspace, where aparameter of the DeleteDatabinData function specifies a particulardatabin. Responsive to the evaluation, computational application 140 mayuse an API to cause the cloud storage management module 190 to deletedata from the specified databin. The cloud storage management module 190may then send a confirmation to the computational application 140, e.g.,using an API, where the confirmation indicates that the data wasdeleted.

Responsive to receiving information from the cloud storage front end 144indicating that the user seeks to delete data in a specified databin(e.g., via one or more API calls), the cloud storage management module190 locates the specified data bin in the cloud storage 180 and deletesdata in the databin.

As discussed above, in some embodiments, the DeleteDatabinData functionincludes an argument that a user can utilize to specify a databin. In anillustrative embodiment, the DeleteDatabinData function has a format asfollows:

DeleteDatabinData [bin], where bin is an argument specifying a unique IDassociated with a databin. In various embodiments, the argument bin canbe of one format or multiple formats, such as one or more of a short ID,a complete UUID, a short URL, a long URL, etc. In some embodiments, theDeleteDatabinData function optionally includes one or more otherarguments that a user can utilize to specify which data in the databinare to be deleted. In an illustrative embodiment, the DeleteDatabinDatafunction has a format as follows:

DeleteDatabinData[bin, params], where bin is the argument specifying aunique ID associated with a databin, and params are one or more otherparameters specifying which data in the databin are to be deleted. Insome embodiments, the one or more other parameters may specify a rangeof entries in terms of an entry index or index range. In someembodiments, the one or more other parameters may specify a range ofentries in terms of time. In some embodiments, the one or more otherparameters may specify a range of entries in terms of keys. In variousembodiments, parameters for specifying databin entries similar to one,several, or none of the parameters for specifying databin entriesdescribed above with respect to the Databin function may be utilized.

The cloud storage management module 190 is configured to utilize the IDin the one or more API calls to locate the specified data bin in thecloud storage 180. Additionally, in some embodiments, the cloud storagemanagement module 190 is configured to utilize other parameters, ifpresent, in the one or more API calls to determine which data in thespecified databin are to be deleted. The cloud storage management module190 then deletes the specified data from the specified databin.

In various embodiments, deleting data from a databin may comprise one ormore of deleting raw data, deleting converted data, deleting metadataassociated with the data, updating metadata to reflect deletion of datafrom a databin, etc.

Referring again to FIG. 1, in some embodiments, the cloud storagemanagement module 190 may be implemented as a multi-threaded servermodule to handle high volume and/or high rate accesses to cloud storageobjects 184. For example, different threads may handle differentrequests to delete data in databins, in an embodiment. As a morespecific example, different threads may handle different requests todelete data in a same databin, in an embodiment.

As another example, different threads additionally or alternatively mayhandle different types of requests regarding the same databin, e.g.,different threads may handle requests to add data to a databin, toaccess data in the same databin, and to delete data in the same databin.

Utilizing Databins with Cloud-Based Development System 188

Referring again to FIG. 1, in some embodiments, databins can be utilizedwith some or more features provided by the cloud-based developmentsystem 188 as described in U.S. patent application Ser. No. 14/549,541,filed Nov. 20, 2014. As merely one illustrative example, theCloudDeploy, FormFunction, and DatabinAdd functions can be utilized todeploy a web form that permits a user or users to add data to a databin.

FIG. 17A illustrates an example programming input 1700 in which aprogrammer utilizes the CloudDeploy, FormFunction, and DatabinAddfunctions to deploy a web form that permits a user or users to add datato a databin. In response, a form generation module of the cloud-baseddevelopment system 188 generates an electronic form object that, whendeployed, includes GUIs for prompting input from a user. The cloud-baseddevelopment system 188 then deploys the form as a web form accessiblevia the Internet.

FIG. 17B illustrates an example form 1750 corresponding to an electronicform object generated by the form generation module cloud-baseddevelopment system 188. The form 1750 includes a pull down menu 1754 forselecting an item from a list, e.g., the list consisting of Breakfast,Lunch, and Dinner. The form 1750 also includes a text box 1758 suitablefor entering an integer. The form 1750 further includes a button 1762.In response to the user selecting the button 1762, the electronic formobject causes data input by the user via the form 1750 to be added to aspecified databin using the DatabinAdd function.

In some embodiments, arguments to functions additionally oralternatively may be in a suitable format different than the formatsdescribed above. For example, in some embodiments, arguments tofunctions may be in formats such as JavaScript Object Notation (JSON),Human-Optimized Config Object Notation (HOCON), YAML, S-expression(symbolic expression), Extensible Markup Language (XML), etc.

Unless specifically stated otherwise, discussions herein using wordssuch as “processing,” “computing,” “calculating,” “determining,”“presenting,” “displaying,” or the like may refer to actions orprocesses of a machine (e.g., a computer) that manipulates or transformsdata represented as physical (e.g., electronic, magnetic, or optical)quantities within one or more memories (e.g., volatile memory,non-volatile memory, or a combination thereof), registers, or othermachine components that receive, store, transmit, or displayinformation.

As used herein any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” or thephrase “in an embodiment” in various places in the specification are notnecessarily all referring to the same embodiment.

Some embodiments may be described using the expression “coupled” and“connected” along with their derivatives. For example, some embodimentsmay be described using the term “coupled” to indicate that two or moreelements are in direct physical or electrical contact. The term“coupled,” however, may also mean that two or more elements are not indirect contact with each other, but yet still co-operate or interactwith each other. The embodiments are not limited in this context.

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

In addition, use of the “a” or “an” are employed to describe elementsand components of the embodiments herein. This is done merely forconvenience and to give a general sense of the description. Thisdescription should be read to include one or at least one and thesingular also includes the plural unless it is obvious that it is meantotherwise.

At least some of the various blocks, operations, and techniquesdescribed above may be implemented utilizing hardware, a processorexecuting firmware instructions, a processor executing softwareinstructions, or any combination thereof. When implemented in hardware,the hardware may comprise one or more of discrete components, anintegrated circuit, an ASIC, a programmable logic device, etc. Whenimplemented utilizing a processor executing software or firmwareinstructions, the software or firmware instructions may be stored in anytangible, non-transitory computer readable medium or media such as amagnetic disk, an optical disk, a tape drive, a RAM, a ROM, a flashmemory, a memory of a processor, etc. Likewise, the software or firmwareinstructions may be delivered to a user or a system via any known ordesired delivery method including, for example, on a tangible,non-transitory computer readable medium or media, or via communicationmedia. The software or firmware instructions may include machinereadable instructions that, when executed by the processor, cause theprocessor to perform various acts.

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for asystem and a process for identifying terminal road segments through thedisclosed principles herein. Thus, while particular embodiments andapplications have been illustrated and described, it is to be understoodthat the disclosed embodiments are not limited to the preciseconstruction and components disclosed herein. Various modifications,changes and variations, which will be apparent to those skilled in theart, may be made in the arrangement, operation and details of the methodand apparatus disclosed herein without departing from the spirit andscope defined in the appended claims.

1. (canceled)
 2. A method for adding data to a cloud storage object forstoring data, the method comprising: receiving, at one or moreprocessors, one or more messages corresponding to a request to add datato an electronic storage object that is accessible on a network, the oneor more messages corresponding to the electronic storage object to whichdata is to be stored, and including raw data corresponding to the datathat is to be stored; and responsive to the one or more messages:locating, at one or more processors, the electronic storage object in adatabase, converting, at one or more processors, the raw data to one ormore symbolic objects that are in a format that is recognized by acomputational application that is configured to evaluate symbolicobjects in the format, and storing the one or more symbolic objects tothe electronic storage object in the database.
 3. The method of claim 2,further comprising: identifying, at one or more processors, dataconversion metadata in the electronic storage object that indicates howthe raw data is to be converted to the one or more symbolic objects;wherein converting the raw data to the one or more symbolic objectscomprises using the data conversion metadata to convert, at one or moreprocessors, the raw data to the one or more symbolic objects.
 4. Themethod of claim 3, wherein: locating the electronic storage objectincludes locating an electronic file system structure corresponding tothe electronic storage object; identifying the data conversion metadatain the electronic storage object includes analyzing a metadata file inthe electronic file system structure, the metadata file storing the dataconversion metadata; and storing the one or more symbolic objectsincludes storing the one or more symbolic objects to a data file in theelectronic file system structure.
 5. The method of claim 4, furthercomprising: storing the raw data to the data file in the electronic filesystem structure responsive to the one or more messages.
 6. The methodof claim 3, wherein: the one or more messages include a key-valueassociation for at least some of the raw data; and using the dataconversion metadata to convert the raw data to the one or more symbolicobjects comprises: identifying, at one or more processors, key-valueassociation metadata in the data conversion metadata that indicates howsymbolic object types are to be associated with keys in the electronicstorage object, and using the key-value association metadata to convertthe at least some of the raw data to the one or more symbolic objects.7. The method of claim 2, further comprising: storing the raw data tothe electronic storage object in the database responsive to the one ormore messages.
 8. The method of claim 7, wherein converting the raw datato the one or more symbolic objects, and storing the one or moresymbolic objects to the electronic storage object are performed afterthe raw data is stored to the electronic storage object.
 9. The methodof claim 8, wherein converting the raw data to the one or more symbolicobjects, and storing the one or more symbolic objects to the electronicstorage object are performed by a background process and also inresponse to the background process determining that the electronicstorage object includes raw data has not yet been converted to the oneor more symbolic objects.
 10. The method of claim 8, wherein convertingthe raw data to the one or more symbolic objects, and storing the one ormore symbolic objects to the electronic storage object are performedalso in response to i) receiving a request to access the electronicstorage object and ii) determining that the electronic storage objectincludes raw data that has not yet been converted to the one or moresymbolic objects.
 11. The method of claim 2, wherein the data conversionmetadata specify one or more symbolic object types, among a plurality ofsymbolic object types recognized by the computational application, towhich the raw data is to be converted.
 12. The method of claim 2,further comprising, responsive to the one or more messages: identifying,at one or more processors, function metadata in the electronic storageobject that indicates one or more processing functions to be performedon the raw data and/or the one or more symbolic objects, and performing,at one or more processors, the one or more processing functions on theraw data and/or the one or more symbolic objects indicated by thefunction metadata in the electronic storage object.
 13. A system,comprising: a network interface device configured to supportcommunications via a communication network; a network-accessiblecomputer storage system; one or more processors coupled to the networkinterface device and the network-accessible computer storage system; andone or more memory devices coupled to the one more processors, the oneor more memory devices storing machine readable instructions that, whenexecuted by the one or more processors, cause the one or more processorsto: receive, via the network interface device, one or more messagescorresponding to requests to add data to an electronic storage objectthat is accessible on a network, the one or more messages correspondingto the electronic storage object to which data is to be stored, andincluding raw data corresponding to the data that is to be stored; andresponsive to the one or more messages: locate the electronic storageobject in the network-accessible computer storage system, convert theraw data to one or more symbolic objects in a format that is recognizedby a computational application that is configured to evaluate symbolicobjects in the format, and store the one or more symbolic objects to theelectronic storage object in the network-accessible computer storagesystem.
 14. The system of claim 13, wherein the one or more memorydevices further store machine readable instructions that, when executedby the one or more processors, cause the one or more processors to:identify data conversion metadata in the electronic storage object thatindicates how the raw data is to be converted to the one or moresymbolic objects, and use the data conversion metadata to convert theraw data to the one or more symbolic objects.
 15. The system of claim14, wherein the one or more memory devices further store machinereadable instructions that, when executed by the one or more processors,cause the one or more processors to: locate an electronic file systemstructure corresponding to the electronic storage object; analyze ametadata file in the electronic file system structure, the metadata filestoring the data conversion metadata; and store the one or more symbolicobjects to a data file in the electronic file system structure.
 16. Thesystem of claim 15, wherein the one or more memory devices further storemachine readable instructions that, when executed by the one or moreprocessors, cause the one or more processors to: store the raw data tothe data file in the electronic file system structure responsive to theone or more messages.
 17. The system of claim 14, wherein: the one ormore messages include a key-value association for at least some of theraw data; and the one or more memory devices further store machinereadable instructions that, when executed by the one or more processors,cause the one or more processors to: identify key-value associationmetadata in the data conversion metadata that indicates how symbolicobject types are to be associated with keys in the electronic storageobject, and use the key-value association metadata to convert the atleast some of the raw data to the one or more symbolic objects.
 18. Thesystem of claim 15, wherein the one or more memory devices further storemachine readable instructions that, when executed by the one or moreprocessors, cause the one or more processors to: store the raw data tothe electronic storage object in the network-accessible computer storagesystem responsive to the one or more messages.
 19. The system of claim18, wherein converting the raw data to the one or more symbolic objects,and storing the one or more symbolic objects to the electronic storageobject are performed after the raw data is stored to the electronicstorage object.
 20. The system of claim 19, wherein converting the rawdata to the one or more symbolic objects, and storing the one or moresymbolic objects to the electronic storage object are performed by abackground process, executed by the one or more processors, and also inresponse to the background process determining that the electronicstorage object includes raw data has not yet been converted to one ormore symbolic objects.
 21. The system of claim 19, wherein convertingthe raw data to the one or more symbolic objects, and storing the one ormore symbolic objects to the electronic storage object are performedalso in response to i) receiving a request to access the electronicstorage object and ii) determining that the electronic storage objectincludes raw data that has not yet been converted to one or moresymbolic objects.
 22. The system of claim 13, wherein the dataconversion metadata specify one or more symbolic object types, among aplurality of symbolic object types recognized by the computationalapplication, to which the raw data is to be converted.
 23. The system ofclaim 13, wherein the one or more memory devices further store machinereadable instructions that, when executed by the one or more processors,cause the one or more processors to, responsive to the one or moremessages: identify function metadata in the electronic storage objectthat indicates one or more processing functions to be performed on theraw data and/or the one or more symbolic objects, and perform the one ormore processing functions on the raw data and/or the one or moresymbolic objects indicated by the function metadata in the electronicstorage object.